├── .gitattributes ├── .github ├── ISSUE_TEMPLATE │ ├── bug_report.yml │ └── feature_request.yml └── workflows │ ├── build-with-all-capacity.yml │ ├── build-with-audio-assistant.yml │ ├── build-with-chatglm.yml │ ├── build-with-latex-arm.yml │ ├── build-with-latex.yml │ ├── build-without-local-llms.yml │ ├── conda-pack-windows.yml │ └── stale.yml ├── .gitignore ├── Dockerfile ├── LICENSE ├── README.md ├── check_proxy.py ├── config.py ├── core_functional.py ├── crazy_functional.py ├── crazy_functions ├── Conversation_To_File.py ├── Image_Generate.py ├── Image_Generate_Wrap.py ├── Internet_GPT.py ├── Internet_GPT_Wrap.py ├── Latex_Function.py ├── Latex_Function_Wrap.py ├── Latex_Project_Polish.py ├── Latex_Project_Translate_Legacy.py ├── Markdown_Translate.py ├── PDF_Translate.py ├── PDF_Translate_Wrap.py ├── Rag_Interface.py ├── Social_Helper.py ├── SourceCode_Analyse.py ├── SourceCode_Comment.py ├── SourceCode_Comment_Wrap.py ├── VideoResource_GPT.py ├── __init__.py ├── agent_fns │ ├── auto_agent.py │ ├── echo_agent.py │ ├── general.py │ ├── persistent.py │ ├── pipe.py │ ├── python_comment_agent.py │ ├── python_comment_compare.html │ └── watchdog.py ├── ast_fns │ └── comment_remove.py ├── crazy_utils.py ├── diagram_fns │ └── file_tree.py ├── doc_fns │ ├── AI_review_doc.py │ ├── __init__.py │ ├── batch_file_query_doc.py │ ├── content_folder.py │ ├── conversation_doc │ │ ├── excel_doc.py │ │ ├── html_doc.py │ │ ├── markdown_doc.py │ │ ├── pdf_doc.py │ │ ├── txt_doc.py │ │ ├── word2pdf.py │ │ └── word_doc.py │ └── read_fns │ │ ├── __init__.py │ │ ├── docx_reader.py │ │ ├── excel_reader.py │ │ ├── markitdown │ │ └── markdown_reader.py │ │ ├── unstructured_all │ │ ├── __init__.py │ │ ├── paper_metadata_extractor.py │ │ ├── paper_structure_extractor.py │ │ ├── unstructured_md.py │ │ └── unstructured_reader.py │ │ └── web_reader.py ├── game_fns │ ├── game_ascii_art.py │ ├── game_interactive_story.py │ └── game_utils.py ├── gen_fns │ └── gen_fns_shared.py ├── ipc_fns │ └── mp.py ├── json_fns │ ├── pydantic_io.py │ └── select_tool.py ├── latex_fns │ ├── latex_actions.py │ ├── latex_pickle_io.py │ └── latex_toolbox.py ├── live_audio │ ├── aliyunASR.py │ └── audio_io.py ├── media_fns │ └── get_media.py ├── multi_stage │ └── multi_stage_utils.py ├── pdf_fns │ ├── breakdown_txt.py │ ├── parse_pdf.py │ ├── parse_pdf_grobid.py │ ├── parse_pdf_legacy.py │ ├── parse_pdf_via_doc2x.py │ ├── parse_word.py │ ├── report_gen_html.py │ ├── report_template.html │ └── report_template_v2.html ├── plugin_template │ └── plugin_class_template.py ├── prompts │ └── internet.py ├── rag_fns │ ├── llama_index_worker.py │ ├── milvus_worker.py │ ├── rag_file_support.py │ └── vector_store_index.py ├── vector_fns │ ├── __init__.py │ ├── general_file_loader.py │ └── vector_database.py ├── vt_fns │ ├── vt_call_plugin.py │ ├── vt_modify_config.py │ └── vt_state.py ├── word_dfa │ └── dfa_algo.py ├── 下载arxiv论文翻译摘要.py ├── 互动小游戏.py ├── 交互功能函数模板.py ├── 函数动态生成.py ├── 命令行助手.py ├── 多智能体.py ├── 总结word文档.py ├── 总结音视频.py ├── 批量总结PDF文档.py ├── 批量总结PDF文档pdfminer.py ├── 批量翻译PDF文档_NOUGAT.py ├── 数学动画生成manim.py ├── 理解PDF文档内容.py ├── 生成函数注释.py ├── 生成多种Mermaid图表.py ├── 知识库问答.py ├── 联网的ChatGPT.py ├── 联网的ChatGPT_bing版.py ├── 虚空终端.py ├── 解析JupyterNotebook.py ├── 询问多个大语言模型.py ├── 语音助手.py ├── 读文章写摘要.py ├── 谷歌检索小助手.py ├── 辅助功能.py └── 高级功能函数模板.py ├── docker-compose.yml ├── docs ├── Dockerfile+ChatGLM ├── Dockerfile+NoLocal+Latex ├── GithubAction+AllCapacity ├── GithubAction+ChatGLM+Moss ├── GithubAction+JittorLLMs ├── GithubAction+NoLocal ├── GithubAction+NoLocal+AudioAssistant ├── GithubAction+NoLocal+Latex ├── GithubAction+NoLocal+Vectordb ├── README.Arabic.md ├── README.English.md ├── README.French.md ├── README.German.md ├── README.Italian.md ├── README.Japanese.md ├── README.Korean.md ├── README.Portuguese.md ├── README.Russian.md ├── WindowsRun.bat ├── WithFastapi.md ├── demo.jpg ├── demo2.jpg ├── logo.png ├── plugin_with_secondary_menu.md ├── self_analysis.md ├── translate_english.json ├── translate_japanese.json ├── translate_std.json ├── translate_traditionalchinese.json ├── use_audio.md ├── use_azure.md ├── use_tts.md └── use_vllm.md ├── main.py ├── multi_language.py ├── request_llms ├── README.md ├── bridge_all.py ├── bridge_chatglm.py ├── bridge_chatglm3.py ├── bridge_chatglm4.py ├── bridge_chatglmft.py ├── bridge_chatglmonnx.py ├── bridge_chatgpt.py ├── bridge_chatgpt_vision.py ├── bridge_claude.py ├── bridge_cohere.py ├── bridge_deepseekcoder.py ├── bridge_google_gemini.py ├── bridge_internlm.py ├── bridge_jittorllms_llama.py ├── bridge_jittorllms_pangualpha.py ├── bridge_jittorllms_rwkv.py ├── bridge_llama2.py ├── bridge_moonshot.py ├── bridge_moss.py ├── bridge_newbingfree.py ├── bridge_ollama.py ├── bridge_openrouter.py ├── bridge_qianfan.py ├── bridge_qwen.py ├── bridge_qwen_local.py ├── bridge_skylark2.py ├── bridge_spark.py ├── bridge_stackclaude.py ├── bridge_taichu.py ├── bridge_tgui.py ├── bridge_zhipu.py ├── chatglmoonx.py ├── com_google.py ├── com_qwenapi.py ├── com_skylark2api.py ├── com_sparkapi.py ├── com_taichu.py ├── com_zhipuglm.py ├── edge_gpt_free.py ├── embed_models │ ├── bridge_all_embed.py │ └── openai_embed.py ├── key_manager.py ├── local_llm_class.py ├── oai_std_model_template.py ├── queued_pipe.py ├── requirements_chatglm.txt ├── requirements_chatglm4.txt ├── requirements_chatglm_onnx.txt ├── requirements_jittorllms.txt ├── requirements_moss.txt ├── requirements_newbing.txt ├── requirements_qwen.txt ├── requirements_qwen_local.txt └── requirements_slackclaude.txt ├── requirements.txt ├── shared_utils ├── advanced_markdown_format.py ├── char_visual_effect.py ├── colorful.py ├── config_loader.py ├── connect_void_terminal.py ├── context_clip_policy.py ├── cookie_manager.py ├── docker_as_service_api.py ├── fastapi_server.py ├── handle_upload.py ├── key_pattern_manager.py ├── logging.py ├── map_names.py └── text_mask.py ├── tests ├── __init__.py ├── init_test.py ├── test_anim_gen.py ├── test_bilibili_down.py ├── test_doc2x.py ├── test_embed.py ├── test_key_pattern_manager.py ├── test_latex_auto_correct.py ├── test_llms.py ├── test_markdown.py ├── test_markdown_format.py ├── test_media.py ├── test_plugins.py ├── test_python_auto_docstring.py ├── test_rag.py ├── test_safe_pickle.py ├── test_save_chat_to_html.py ├── test_searxng.py ├── test_social_helper.py ├── test_tts.py ├── test_utils.py └── test_vector_plugins.py ├── themes ├── base64.mjs ├── common.css ├── common.js ├── common.py ├── contrast.css ├── contrast.py ├── cookies.py ├── default.css ├── default.py ├── gradios.py ├── green.css ├── green.js ├── green.py ├── gui_advanced_plugin_class.py ├── gui_floating_menu.py ├── gui_toolbar.py ├── init.js ├── svg │ ├── arxiv.svg │ ├── box.svg │ ├── brain.svg │ ├── check.svg │ ├── conf.svg │ ├── default.svg │ ├── doc.svg │ ├── img.svg │ ├── location.svg │ ├── mm.svg │ ├── polish.svg │ ├── tts.svg │ └── vt.svg ├── theme.js ├── theme.py ├── tts.js ├── waifu_plugin │ ├── autoload.js │ ├── flat-ui-icons-regular.eot │ ├── flat-ui-icons-regular.svg │ ├── flat-ui-icons-regular.ttf │ ├── flat-ui-icons-regular.woff │ ├── jquery-ui.min.js │ ├── jquery.min.js │ ├── live2d.js │ ├── source │ ├── waifu-tips.js │ ├── waifu-tips.json │ └── waifu.css └── welcome.js ├── toolbox.py └── version /.gitattributes: -------------------------------------------------------------------------------- 1 | *.h linguist-detectable=false 2 | *.cpp linguist-detectable=false 3 | *.tex linguist-detectable=false 4 | *.cs linguist-detectable=false 5 | *.tps linguist-detectable=false 6 | -------------------------------------------------------------------------------- /.github/ISSUE_TEMPLATE/bug_report.yml: -------------------------------------------------------------------------------- 1 | name: Report Bug | 报告BUG 2 | description: "Report bug" 3 | title: "[Bug]: " 4 | labels: [] 5 | body: 6 | - type: dropdown 7 | id: download 8 | attributes: 9 | label: Installation Method | 安装方法与平台 10 | options: 11 | - Please choose | 请选择 12 | - Pip Install (I ignored requirements.txt) 13 | - Pip Install (I used latest requirements.txt) 14 | - OneKeyInstall (一键安装脚本-windows) 15 | - OneKeyInstall (一键安装脚本-mac) 16 | - Anaconda (I ignored requirements.txt) 17 | - Anaconda (I used latest requirements.txt) 18 | - Docker（Windows/Mac） 19 | - Docker（Linux） 20 | - Docker-Compose（Windows/Mac） 21 | - Docker-Compose（Linux） 22 | - Huggingface 23 | - Others (Please Describe) 24 | validations: 25 | required: true 26 | 27 | - type: dropdown 28 | id: version 29 | attributes: 30 | label: Version | 版本 31 | options: 32 | - Please choose | 请选择 33 | - Latest | 最新版 34 | - Others | 非最新版 35 | validations: 36 | required: true 37 | 38 | - type: dropdown 39 | id: os 40 | attributes: 41 | label: OS | 操作系统 42 | options: 43 | - Please choose | 请选择 44 | - Windows 45 | - Mac 46 | - Linux 47 | - Docker 48 | validations: 49 | required: true 50 | 51 | - type: textarea 52 | id: describe 53 | attributes: 54 | label: Describe the bug | 简述 55 | description: Describe the bug | 简述 56 | validations: 57 | required: true 58 | 59 | - type: textarea 60 | id: screenshot 61 | attributes: 62 | label: Screen Shot | 有帮助的截图 63 | description: Screen Shot | 有帮助的截图 64 | validations: 65 | required: true 66 | 67 | - type: textarea 68 | id: traceback 69 | attributes: 70 | label: Terminal Traceback & Material to Help Reproduce Bugs | 终端traceback（如有） + 帮助我们复现的测试材料样本（如有） 71 | description: Terminal Traceback & Material to Help Reproduce Bugs | 终端traceback（如有） + 帮助我们复现的测试材料样本（如有） 72 | -------------------------------------------------------------------------------- /.github/ISSUE_TEMPLATE/feature_request.yml: -------------------------------------------------------------------------------- 1 | name: Feature Request | 功能请求 2 | description: "Feature Request" 3 | title: "[Feature]: " 4 | labels: [] 5 | body: 6 | - type: dropdown 7 | id: download 8 | attributes: 9 | label: Class | 类型 10 | options: 11 | - Please choose | 请选择 12 | - 其他 13 | - 函数插件 14 | - 大语言模型 15 | - 程序主体 16 | validations: 17 | required: false 18 | 19 | - type: textarea 20 | id: traceback 21 | attributes: 22 | label: Feature Request | 功能请求 23 | description: Feature Request | 功能请求 24 | -------------------------------------------------------------------------------- /.github/workflows/build-with-all-capacity.yml: -------------------------------------------------------------------------------- 1 | # https://docs.github.com/en/actions/publishing-packages/publishing-docker-images#publishing-images-to-github-packages 2 | name: build-with-all-capacity 3 | 4 | on: 5 | push: 6 | branches: 7 | - 'master' 8 | 9 | env: 10 | REGISTRY: ghcr.io 11 | IMAGE_NAME: ${{ github.repository }}_with_all_capacity 12 | 13 | jobs: 14 | build-and-push-image: 15 | runs-on: ubuntu-latest 16 | permissions: 17 | contents: read 18 | packages: write 19 | 20 | steps: 21 | - name: Checkout repository 22 | uses: actions/checkout@v3 23 | 24 | - name: Log in to the Container registry 25 | uses: docker/login-action@v2 26 | with: 27 | registry: ${{ env.REGISTRY }} 28 | username: ${{ github.actor }} 29 | password: ${{ secrets.GITHUB_TOKEN }} 30 | 31 | - name: Extract metadata (tags, labels) for Docker 32 | id: meta 33 | uses: docker/metadata-action@v4 34 | with: 35 | images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }} 36 | 37 | - name: Build and push Docker image 38 | uses: docker/build-push-action@v4 39 | with: 40 | context: . 41 | push: true 42 | file: docs/GithubAction+AllCapacity 43 | tags: ${{ steps.meta.outputs.tags }} 44 | labels: ${{ steps.meta.outputs.labels }} 45 | -------------------------------------------------------------------------------- /.github/workflows/build-with-audio-assistant.yml: -------------------------------------------------------------------------------- 1 | # https://docs.github.com/en/actions/publishing-packages/publishing-docker-images#publishing-images-to-github-packages 2 | name: build-with-audio-assistant 3 | 4 | on: 5 | push: 6 | branches: 7 | - 'master' 8 | 9 | env: 10 | REGISTRY: ghcr.io 11 | IMAGE_NAME: ${{ github.repository }}_audio_assistant 12 | 13 | jobs: 14 | build-and-push-image: 15 | runs-on: ubuntu-latest 16 | permissions: 17 | contents: read 18 | packages: write 19 | 20 | steps: 21 | - name: Checkout repository 22 | uses: actions/checkout@v3 23 | 24 | - name: Log in to the Container registry 25 | uses: docker/login-action@v2 26 | with: 27 | registry: ${{ env.REGISTRY }} 28 | username: ${{ github.actor }} 29 | password: ${{ secrets.GITHUB_TOKEN }} 30 | 31 | - name: Extract metadata (tags, labels) for Docker 32 | id: meta 33 | uses: docker/metadata-action@v4 34 | with: 35 | images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }} 36 | 37 | - name: Build and push Docker image 38 | uses: docker/build-push-action@v4 39 | with: 40 | context: . 41 | push: true 42 | file: docs/GithubAction+NoLocal+AudioAssistant 43 | tags: ${{ steps.meta.outputs.tags }} 44 | labels: ${{ steps.meta.outputs.labels }} 45 | -------------------------------------------------------------------------------- /.github/workflows/build-with-chatglm.yml: -------------------------------------------------------------------------------- 1 | # https://docs.github.com/en/actions/publishing-packages/publishing-docker-images#publishing-images-to-github-packages 2 | name: build-with-chatglm 3 | 4 | on: 5 | push: 6 | branches: 7 | - 'master' 8 | 9 | env: 10 | REGISTRY: ghcr.io 11 | IMAGE_NAME: ${{ github.repository }}_chatglm_moss 12 | 13 | jobs: 14 | build-and-push-image: 15 | runs-on: ubuntu-latest 16 | permissions: 17 | contents: read 18 | packages: write 19 | 20 | steps: 21 | - name: Checkout repository 22 | uses: actions/checkout@v3 23 | 24 | - name: Log in to the Container registry 25 | uses: docker/login-action@v2 26 | with: 27 | registry: ${{ env.REGISTRY }} 28 | username: ${{ github.actor }} 29 | password: ${{ secrets.GITHUB_TOKEN }} 30 | 31 | - name: Extract metadata (tags, labels) for Docker 32 | id: meta 33 | uses: docker/metadata-action@v4 34 | with: 35 | images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }} 36 | 37 | - name: Build and push Docker image 38 | uses: docker/build-push-action@v4 39 | with: 40 | context: . 41 | push: true 42 | file: docs/GithubAction+ChatGLM+Moss 43 | tags: ${{ steps.meta.outputs.tags }} 44 | labels: ${{ steps.meta.outputs.labels }} 45 | -------------------------------------------------------------------------------- /.github/workflows/build-with-latex-arm.yml: -------------------------------------------------------------------------------- 1 | # https://docs.github.com/en/actions/publishing-packages/publishing-docker-images#publishing-images-to-github-packages 2 | name: build-with-latex-arm 3 | 4 | on: 5 | push: 6 | branches: 7 | - "master" 8 | 9 | env: 10 | REGISTRY: ghcr.io 11 | IMAGE_NAME: ${{ github.repository }}_with_latex_arm 12 | 13 | jobs: 14 | build-and-push-image: 15 | runs-on: ubuntu-latest 16 | permissions: 17 | contents: read 18 | packages: write 19 | 20 | steps: 21 | - name: Set up QEMU 22 | uses: docker/setup-qemu-action@v3 23 | 24 | - name: Set up Docker Buildx 25 | uses: docker/setup-buildx-action@v3 26 | 27 | - name: Checkout repository 28 | uses: actions/checkout@v4 29 | 30 | - name: Log in to the Container registry 31 | uses: docker/login-action@v3 32 | with: 33 | registry: ${{ env.REGISTRY }} 34 | username: ${{ github.actor }} 35 | password: ${{ secrets.GITHUB_TOKEN }} 36 | 37 | - name: Extract metadata (tags, labels) for Docker 38 | id: meta 39 | uses: docker/metadata-action@v4 40 | with: 41 | images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }} 42 | 43 | - name: Build and push Docker image 44 | uses: docker/build-push-action@v6 45 | with: 46 | context: . 47 | push: true 48 | platforms: linux/arm64 49 | file: docs/GithubAction+NoLocal+Latex 50 | tags: ${{ steps.meta.outputs.tags }} 51 | labels: ${{ steps.meta.outputs.labels }} -------------------------------------------------------------------------------- /.github/workflows/build-with-latex.yml: -------------------------------------------------------------------------------- 1 | # https://docs.github.com/en/actions/publishing-packages/publishing-docker-images#publishing-images-to-github-packages 2 | name: build-with-latex 3 | 4 | on: 5 | push: 6 | branches: 7 | - 'master' 8 | 9 | env: 10 | REGISTRY: ghcr.io 11 | IMAGE_NAME: ${{ github.repository }}_with_latex 12 | 13 | jobs: 14 | build-and-push-image: 15 | runs-on: ubuntu-latest 16 | permissions: 17 | contents: read 18 | packages: write 19 | 20 | steps: 21 | - name: Checkout repository 22 | uses: actions/checkout@v3 23 | 24 | - name: Log in to the Container registry 25 | uses: docker/login-action@v2 26 | with: 27 | registry: ${{ env.REGISTRY }} 28 | username: ${{ github.actor }} 29 | password: ${{ secrets.GITHUB_TOKEN }} 30 | 31 | - name: Extract metadata (tags, labels) for Docker 32 | id: meta 33 | uses: docker/metadata-action@v4 34 | with: 35 | images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }} 36 | 37 | - name: Build and push Docker image 38 | uses: docker/build-push-action@v4 39 | with: 40 | context: . 41 | push: true 42 | file: docs/GithubAction+NoLocal+Latex 43 | tags: ${{ steps.meta.outputs.tags }} 44 | labels: ${{ steps.meta.outputs.labels }} 45 | -------------------------------------------------------------------------------- /.github/workflows/build-without-local-llms.yml: -------------------------------------------------------------------------------- 1 | # https://docs.github.com/en/actions/publishing-packages/publishing-docker-images#publishing-images-to-github-packages 2 | name: build-without-local-llms 3 | 4 | on: 5 | push: 6 | branches: 7 | - 'master' 8 | 9 | env: 10 | REGISTRY: ghcr.io 11 | IMAGE_NAME: ${{ github.repository }}_nolocal 12 | 13 | jobs: 14 | build-and-push-image: 15 | runs-on: ubuntu-latest 16 | permissions: 17 | contents: read 18 | packages: write 19 | 20 | steps: 21 | - name: Checkout repository 22 | uses: actions/checkout@v3 23 | 24 | - name: Log in to the Container registry 25 | uses: docker/login-action@v2 26 | with: 27 | registry: ${{ env.REGISTRY }} 28 | username: ${{ github.actor }} 29 | password: ${{ secrets.GITHUB_TOKEN }} 30 | 31 | - name: Extract metadata (tags, labels) for Docker 32 | id: meta 33 | uses: docker/metadata-action@v4 34 | with: 35 | images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }} 36 | 37 | - name: Build and push Docker image 38 | uses: docker/build-push-action@v4 39 | with: 40 | context: . 41 | push: true 42 | file: docs/GithubAction+NoLocal 43 | tags: ${{ steps.meta.outputs.tags }} 44 | labels: ${{ steps.meta.outputs.labels }} 45 | -------------------------------------------------------------------------------- /.github/workflows/conda-pack-windows.yml: -------------------------------------------------------------------------------- 1 | name: Create Conda Environment Package 2 | 3 | on: 4 | workflow_dispatch: 5 | 6 | jobs: 7 | build: 8 | runs-on: windows-latest 9 | 10 | steps: 11 | - name: Checkout repository 12 | uses: actions/checkout@v4 13 | 14 | - name: Setup Miniconda 15 | uses: conda-incubator/setup-miniconda@v3 16 | with: 17 | auto-activate-base: true 18 | activate-environment: "" 19 | 20 | - name: Create new Conda environment 21 | shell: bash -l {0} 22 | run: | 23 | conda create -n gpt python=3.11 -y 24 | conda activate gpt 25 | 26 | - name: Install requirements 27 | shell: bash -l {0} 28 | run: | 29 | conda activate gpt 30 | pip install -r requirements.txt 31 | 32 | - name: Install conda-pack 33 | shell: bash -l {0} 34 | run: | 35 | conda activate gpt 36 | conda install conda-pack -y 37 | 38 | - name: Pack conda environment 39 | shell: bash -l {0} 40 | run: | 41 | conda activate gpt 42 | conda pack -n gpt -o gpt.tar.gz 43 | 44 | - name: Create workspace zip 45 | shell: pwsh 46 | run: | 47 | mkdir workspace 48 | Get-ChildItem -Exclude "workspace" | Copy-Item -Destination workspace -Recurse 49 | Remove-Item -Path workspace/.git* -Recurse -Force -ErrorAction SilentlyContinue 50 | Copy-Item gpt.tar.gz workspace/ -Force 51 | 52 | - name: Upload packed files 53 | uses: actions/upload-artifact@v4 54 | with: 55 | name: gpt-academic-package 56 | path: workspace 57 | -------------------------------------------------------------------------------- /.github/workflows/stale.yml: -------------------------------------------------------------------------------- 1 | # This workflow warns and then closes issues and PRs that have had no activity for a specified amount of time. 2 | # 3 | # You can adjust the behavior by modifying this file. 4 | # For more information, see: 5 | # https://github.com/actions/stale 6 | 7 | name: 'Close stale issues and PRs' 8 | on: 9 | schedule: 10 | - cron: '*/30 * * * *' 11 | 12 | jobs: 13 | stale: 14 | runs-on: ubuntu-latest 15 | permissions: 16 | issues: write 17 | pull-requests: read 18 | 19 | steps: 20 | - uses: actions/stale@v8 21 | with: 22 | stale-issue-message: 'This issue is stale because it has been open 100 days with no activity. Remove stale label or comment or this will be closed in 7 days.' 23 | days-before-stale: 100 24 | days-before-close: 7 25 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | pip-wheel-metadata/ 24 | share/python-wheels/ 25 | *.egg-info/ 26 | .installed.cfg 27 | *.egg 28 | MANIFEST 29 | 30 | # PyInstaller 31 | # Usually these files are written by a python script from a template 32 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 33 | *.manifest 34 | *.spec 35 | # Installer logs 36 | pip-log.txt 37 | pip-delete-this-directory.txt 38 | 39 | # Unit test / coverage reports 40 | htmlcov/ 41 | .tox/ 42 | .nox/ 43 | .coverage 44 | .coverage.* 45 | .cache 46 | nosetests.xml 47 | coverage.xml 48 | *.cover 49 | *.py,cover 50 | .hypothesis/ 51 | .pytest_cache/ 52 | 53 | # Translations 54 | *.mo 55 | *.pot 56 | github 57 | .github 58 | TEMP 59 | TRASH 60 | 61 | # Django stuff: 62 | *.log 63 | local_settings.py 64 | db.sqlite3 65 | db.sqlite3-journal 66 | 67 | # Flask stuff: 68 | instance/ 69 | .webassets-cache 70 | 71 | # Scrapy stuff: 72 | .scrapy 73 | 74 | # Sphinx documentation 75 | docs/_build/ 76 | 77 | # PyBuilder 78 | target/ 79 | 80 | # Jupyter Notebook 81 | .ipynb_checkpoints 82 | 83 | # IPython 84 | profile_default/ 85 | ipython_config.py 86 | 87 | # pyenv 88 | .python-version 89 | 90 | # pipenv 91 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 92 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 93 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 94 | # install all needed dependencies. 95 | #Pipfile.lock 96 | 97 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow 98 | __pypackages__/ 99 | 100 | # Celery stuff 101 | celerybeat-schedule 102 | celerybeat.pid 103 | 104 | # SageMath parsed files 105 | *.sage.py 106 | 107 | # Environments 108 | .env 109 | .venv 110 | env/ 111 | venv/ 112 | ENV/ 113 | env.bak/ 114 | venv.bak/ 115 | 116 | # Spyder project settings 117 | .spyderproject 118 | .spyproject 119 | 120 | # Rope project settings 121 | .ropeproject 122 | 123 | # mkdocs documentation 124 | /site 125 | 126 | # mypy 127 | .mypy_cache/ 128 | .dmypy.json 129 | dmypy.json 130 | 131 | # Pyre type checker 132 | .pyre/ 133 | 134 | # macOS files 135 | .DS_Store 136 | 137 | .vscode 138 | .idea 139 | 140 | history 141 | ssr_conf 142 | config_private.py 143 | gpt_log 144 | private.md 145 | private_upload 146 | other_llms 147 | cradle* 148 | debug* 149 | private* 150 | crazy_functions/test_project/pdf_and_word 151 | crazy_functions/test_samples 152 | request_llms/jittorllms 153 | multi-language 154 | request_llms/moss 155 | media 156 | flagged 157 | request_llms/ChatGLM-6b-onnx-u8s8 158 | .pre-commit-config.yaml 159 | test.* 160 | temp.* 161 | objdump* 162 | *.min.*.js 163 | TODO 164 | experimental_mods 165 | search_results 166 | -------------------------------------------------------------------------------- /Dockerfile: -------------------------------------------------------------------------------- 1 | # 此Dockerfile适用于“无本地模型”的迷你运行环境构建 2 | # 如果需要使用chatglm等本地模型或者latex运行依赖，请参考 docker-compose.yml 3 | # - 如何构建: 先修改 `config.py`， 然后 `docker build -t gpt-academic . ` 4 | # - 如何运行(Linux下): `docker run --rm -it --net=host gpt-academic ` 5 | # - 如何运行(其他操作系统，选择任意一个固定端口50923): `docker run --rm -it -e WEB_PORT=50923 -p 50923:50923 gpt-academic ` 6 | 7 | FROM ghcr.io/astral-sh/uv:python3.12-bookworm 8 | 9 | # 非必要步骤，更换pip源 （以下三行，可以删除） 10 | RUN echo '[global]' > /etc/pip.conf && \ 11 | echo 'index-url = https://mirrors.aliyun.com/pypi/simple/' >> /etc/pip.conf && \ 12 | echo 'trusted-host = mirrors.aliyun.com' >> /etc/pip.conf 13 | 14 | # 语音输出功能（以下1,2行更换阿里源，第3,4行安装ffmpeg，都可以删除） 15 | RUN sed -i 's/deb.debian.org/mirrors.aliyun.com/g' /etc/apt/sources.list.d/debian.sources && \ 16 | sed -i 's/security.debian.org/mirrors.aliyun.com/g' /etc/apt/sources.list.d/debian.sources && \ 17 | apt-get update 18 | RUN apt-get install ffmpeg -y 19 | RUN apt-get clean 20 | 21 | # 进入工作路径（必要） 22 | WORKDIR /gpt 23 | 24 | # 安装大部分依赖，利用Docker缓存加速以后的构建 （以下两行，可以删除） 25 | COPY requirements.txt ./ 26 | RUN uv venv --python=3.12 && uv pip install --verbose -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/ 27 | ENV PATH="/gpt/.venv/bin:$PATH" 28 | RUN python -c 'import loguru' 29 | 30 | # 装载项目文件，安装剩余依赖（必要） 31 | COPY . . 32 | RUN uv venv --python=3.12 && uv pip install -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/ 33 | 34 | # # 非必要步骤，用于预热模块（可以删除） 35 | RUN python -c 'from check_proxy import warm_up_modules; warm_up_modules()' 36 | 37 | # 启动（必要） 38 | CMD ["bash", "-c", "python main.py"] 39 | -------------------------------------------------------------------------------- /crazy_functions/Image_Generate_Wrap.py: -------------------------------------------------------------------------------- 1 | 2 | from toolbox import get_conf, update_ui 3 | from crazy_functions.Image_Generate import 图片生成_DALLE2, 图片生成_DALLE3, 图片修改_DALLE2 4 | from crazy_functions.plugin_template.plugin_class_template import GptAcademicPluginTemplate, ArgProperty 5 | 6 | 7 | class ImageGen_Wrap(GptAcademicPluginTemplate): 8 | def __init__(self): 9 | """ 10 | 请注意`execute`会执行在不同的线程中，因此您在定义和使用类变量时，应当慎之又慎！ 11 | """ 12 | pass 13 | 14 | def define_arg_selection_menu(self): 15 | """ 16 | 定义插件的二级选项菜单 17 | 18 | 第一个参数，名称`main_input`，参数`type`声明这是一个文本框，文本框上方显示`title`，文本框内部显示`description`，`default_value`为默认值； 19 | 第二个参数，名称`advanced_arg`，参数`type`声明这是一个文本框，文本框上方显示`title`，文本框内部显示`description`，`default_value`为默认值； 20 | 21 | """ 22 | gui_definition = { 23 | "main_input": 24 | ArgProperty(title="输入图片描述", description="需要生成图像的文本描述，尽量使用英文", default_value="", type="string").model_dump_json(), # 主输入，自动从输入框同步 25 | "model_name": 26 | ArgProperty(title="模型", options=["DALLE2", "DALLE3"], default_value="DALLE3", description="无", type="dropdown").model_dump_json(), 27 | "resolution": 28 | ArgProperty(title="分辨率", options=["256x256(限DALLE2)", "512x512(限DALLE2)", "1024x1024", "1792x1024(限DALLE3)", "1024x1792(限DALLE3)"], default_value="1024x1024", description="无", type="dropdown").model_dump_json(), 29 | "quality (仅DALLE3生效)": 30 | ArgProperty(title="质量", options=["standard", "hd"], default_value="standard", description="无", type="dropdown").model_dump_json(), 31 | "style (仅DALLE3生效)": 32 | ArgProperty(title="风格", options=["vivid", "natural"], default_value="vivid", description="无", type="dropdown").model_dump_json(), 33 | 34 | } 35 | return gui_definition 36 | 37 | def execute(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request): 38 | """ 39 | 执行插件 40 | """ 41 | # 分辨率 42 | resolution = plugin_kwargs["resolution"].replace("(限DALLE2)", "").replace("(限DALLE3)", "") 43 | 44 | if plugin_kwargs["model_name"] == "DALLE2": 45 | plugin_kwargs["advanced_arg"] = resolution 46 | yield from 图片生成_DALLE2(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request) 47 | 48 | elif plugin_kwargs["model_name"] == "DALLE3": 49 | quality = plugin_kwargs["quality (仅DALLE3生效)"] 50 | style = plugin_kwargs["style (仅DALLE3生效)"] 51 | plugin_kwargs["advanced_arg"] = f"{resolution}-{quality}-{style}" 52 | yield from 图片生成_DALLE3(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request) 53 | 54 | else: 55 | chatbot.append([None, "抱歉，找不到该模型"]) 56 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 57 | -------------------------------------------------------------------------------- /crazy_functions/Internet_GPT_Wrap.py: -------------------------------------------------------------------------------- 1 | import random 2 | from toolbox import get_conf 3 | from crazy_functions.Internet_GPT import 连接网络回答问题 4 | from crazy_functions.plugin_template.plugin_class_template import GptAcademicPluginTemplate, ArgProperty 5 | 6 | 7 | class NetworkGPT_Wrap(GptAcademicPluginTemplate): 8 | def __init__(self): 9 | """ 10 | 请注意`execute`会执行在不同的线程中，因此您在定义和使用类变量时，应当慎之又慎！ 11 | """ 12 | pass 13 | 14 | def define_arg_selection_menu(self): 15 | """ 16 | 定义插件的二级选项菜单 17 | 18 | 第一个参数，名称`main_input`，参数`type`声明这是一个文本框，文本框上方显示`title`，文本框内部显示`description`，`default_value`为默认值； 19 | 第二个参数，名称`advanced_arg`，参数`type`声明这是一个文本框，文本框上方显示`title`，文本框内部显示`description`，`default_value`为默认值； 20 | 第三个参数，名称`allow_cache`，参数`type`声明这是一个下拉菜单，下拉菜单上方显示`title`+`description`，下拉菜单的选项为`options`，`default_value`为下拉菜单默认值； 21 | 22 | """ 23 | urls = get_conf("SEARXNG_URLS") 24 | url = random.choice(urls) 25 | 26 | gui_definition = { 27 | "main_input": 28 | ArgProperty(title="输入问题", description="待通过互联网检索的问题，会自动读取输入框内容", default_value="", type="string").model_dump_json(), # 主输入，自动从输入框同步 29 | "categories": 30 | ArgProperty(title="搜索分类", options=["网页", "学术论文"], default_value="网页", description="无", type="dropdown").model_dump_json(), 31 | "engine": 32 | ArgProperty(title="选择搜索引擎", options=["Mixed", "bing", "google", "duckduckgo"], default_value="google", description="无", type="dropdown").model_dump_json(), 33 | "optimizer": 34 | ArgProperty(title="搜索优化", options=["关闭", "开启", "开启(增强)"], default_value="关闭", description="是否使用搜索增强。注意这可能会消耗较多token", type="dropdown").model_dump_json(), 35 | "searxng_url": 36 | ArgProperty(title="Searxng服务地址", description="输入Searxng的地址", default_value=url, type="string").model_dump_json(), # 主输入，自动从输入框同步 37 | 38 | } 39 | return gui_definition 40 | 41 | def execute(txt, llm_kwargs, plugin_kwargs:dict, chatbot, history, system_prompt, user_request): 42 | """ 43 | 执行插件 44 | """ 45 | if plugin_kwargs.get("categories", None) == "网页": plugin_kwargs["categories"] = "general" 46 | elif plugin_kwargs.get("categories", None) == "学术论文": plugin_kwargs["categories"] = "science" 47 | else: plugin_kwargs["categories"] = "general" 48 | yield from 连接网络回答问题(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request) 49 | 50 | -------------------------------------------------------------------------------- /crazy_functions/PDF_Translate_Wrap.py: -------------------------------------------------------------------------------- 1 | from crazy_functions.plugin_template.plugin_class_template import GptAcademicPluginTemplate, ArgProperty 2 | from .PDF_Translate import 批量翻译PDF文档 3 | 4 | 5 | class PDF_Tran(GptAcademicPluginTemplate): 6 | def __init__(self): 7 | """ 8 | 请注意`execute`会执行在不同的线程中，因此您在定义和使用类变量时，应当慎之又慎！ 9 | """ 10 | pass 11 | 12 | def define_arg_selection_menu(self): 13 | """ 14 | 定义插件的二级选项菜单 15 | """ 16 | gui_definition = { 17 | "main_input": 18 | ArgProperty(title="PDF文件路径", description="未指定路径，请上传文件后，再点击该插件", default_value="", type="string").model_dump_json(), # 主输入，自动从输入框同步 19 | "additional_prompt": 20 | ArgProperty(title="额外提示词", description="例如：对专有名词、翻译语气等方面的要求", default_value="", type="string").model_dump_json(), # 高级参数输入区，自动同步 21 | "pdf_parse_method": 22 | ArgProperty(title="PDF解析方法", options=["DOC2X", "GROBID", "Classic"], description="无", default_value="GROBID", type="dropdown").model_dump_json(), 23 | } 24 | return gui_definition 25 | 26 | def execute(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request): 27 | """ 28 | 执行插件 29 | """ 30 | main_input = plugin_kwargs["main_input"] 31 | additional_prompt = plugin_kwargs["additional_prompt"] 32 | pdf_parse_method = plugin_kwargs["pdf_parse_method"] 33 | yield from 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request) -------------------------------------------------------------------------------- /crazy_functions/SourceCode_Comment_Wrap.py: -------------------------------------------------------------------------------- 1 | 2 | from toolbox import get_conf, update_ui 3 | from crazy_functions.plugin_template.plugin_class_template import GptAcademicPluginTemplate, ArgProperty 4 | from crazy_functions.SourceCode_Comment import 注释Python项目 5 | 6 | class SourceCodeComment_Wrap(GptAcademicPluginTemplate): 7 | def __init__(self): 8 | """ 9 | 请注意`execute`会执行在不同的线程中，因此您在定义和使用类变量时，应当慎之又慎！ 10 | """ 11 | pass 12 | 13 | def define_arg_selection_menu(self): 14 | """ 15 | 定义插件的二级选项菜单 16 | """ 17 | gui_definition = { 18 | "main_input": 19 | ArgProperty(title="路径", description="程序路径（上传文件后自动填写）", default_value="", type="string").model_dump_json(), # 主输入，自动从输入框同步 20 | "use_chinese": 21 | ArgProperty(title="注释语言", options=["英文", "中文"], default_value="英文", description="无", type="dropdown").model_dump_json(), 22 | # "use_emoji": 23 | # ArgProperty(title="在注释中使用emoji", options=["禁止", "允许"], default_value="禁止", description="无", type="dropdown").model_dump_json(), 24 | } 25 | return gui_definition 26 | 27 | def execute(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request): 28 | """ 29 | 执行插件 30 | """ 31 | if plugin_kwargs["use_chinese"] == "中文": 32 | plugin_kwargs["use_chinese"] = True 33 | else: 34 | plugin_kwargs["use_chinese"] = False 35 | 36 | yield from 注释Python项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request) 37 | -------------------------------------------------------------------------------- /crazy_functions/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/binary-husky/gpt_academic/8c2143229113ad0953b4e4dfd2a543292ce65b14/crazy_functions/__init__.py -------------------------------------------------------------------------------- /crazy_functions/agent_fns/auto_agent.py: -------------------------------------------------------------------------------- 1 | from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, ProxyNetworkActivate 2 | from toolbox import report_exception, get_log_folder, update_ui_latest_msg, Singleton 3 | from crazy_functions.agent_fns.pipe import PluginMultiprocessManager, PipeCom 4 | from crazy_functions.agent_fns.general import AutoGenGeneral 5 | 6 | 7 | 8 | class AutoGenMath(AutoGenGeneral): 9 | 10 | def define_agents(self): 11 | from autogen import AssistantAgent, UserProxyAgent 12 | return [ 13 | { 14 | "name": "assistant", # name of the agent. 15 | "cls": AssistantAgent, # class of the agent. 16 | }, 17 | { 18 | "name": "user_proxy", # name of the agent. 19 | "cls": UserProxyAgent, # class of the agent. 20 | "human_input_mode": "ALWAYS", # always ask for human input. 21 | "llm_config": False, # disables llm-based auto reply. 22 | }, 23 | ] -------------------------------------------------------------------------------- /crazy_functions/agent_fns/echo_agent.py: -------------------------------------------------------------------------------- 1 | from crazy_functions.agent_fns.pipe import PluginMultiprocessManager, PipeCom 2 | from loguru import logger 3 | 4 | class EchoDemo(PluginMultiprocessManager): 5 | def subprocess_worker(self, child_conn): 6 | # ⭐⭐ 子进程 7 | self.child_conn = child_conn 8 | while True: 9 | msg = self.child_conn.recv() # PipeCom 10 | if msg.cmd == "user_input": 11 | # wait father user input 12 | self.child_conn.send(PipeCom("show", msg.content)) 13 | wait_success = self.subprocess_worker_wait_user_feedback(wait_msg="我准备好处理下一个问题了.") 14 | if not wait_success: 15 | # wait timeout, terminate this subprocess_worker 16 | break 17 | elif msg.cmd == "terminate": 18 | self.child_conn.send(PipeCom("done", "")) 19 | break 20 | logger.info('[debug] subprocess_worker terminated') -------------------------------------------------------------------------------- /crazy_functions/agent_fns/persistent.py: -------------------------------------------------------------------------------- 1 | from toolbox import Singleton 2 | @Singleton 3 | class GradioMultiuserManagerForPersistentClasses(): 4 | def __init__(self): 5 | self.mapping = {} 6 | 7 | def already_alive(self, key): 8 | return (key in self.mapping) and (self.mapping[key].is_alive()) 9 | 10 | def set(self, key, x): 11 | self.mapping[key] = x 12 | return self.mapping[key] 13 | 14 | def get(self, key): 15 | return self.mapping[key] 16 | 17 | -------------------------------------------------------------------------------- /crazy_functions/agent_fns/python_comment_compare.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 源文件对比 7 | 34 | 35 | 36 |
37 |
38 | REPLACE_CODE_FILE_LEFT 39 |
40 |
41 | REPLACE_CODE_FILE_RIGHT 42 |
43 |
44 | 45 | -------------------------------------------------------------------------------- /crazy_functions/agent_fns/watchdog.py: -------------------------------------------------------------------------------- 1 | import threading, time 2 | from loguru import logger 3 | 4 | class WatchDog(): 5 | def __init__(self, timeout, bark_fn, interval=3, msg="") -> None: 6 | self.last_feed = None 7 | self.timeout = timeout 8 | self.bark_fn = bark_fn 9 | self.interval = interval 10 | self.msg = msg 11 | self.kill_dog = False 12 | 13 | def watch(self): 14 | while True: 15 | if self.kill_dog: break 16 | if time.time() - self.last_feed > self.timeout: 17 | if len(self.msg) > 0: logger.info(self.msg) 18 | self.bark_fn() 19 | break 20 | time.sleep(self.interval) 21 | 22 | def begin_watch(self): 23 | self.last_feed = time.time() 24 | th = threading.Thread(target=self.watch) 25 | th.daemon = True 26 | th.start() 27 | 28 | def feed(self): 29 | self.last_feed = time.time() 30 | -------------------------------------------------------------------------------- /crazy_functions/ast_fns/comment_remove.py: -------------------------------------------------------------------------------- 1 | import token 2 | import tokenize 3 | import copy 4 | import io 5 | 6 | 7 | def remove_python_comments(input_source: str) -> str: 8 | source_flag = copy.copy(input_source) 9 | source = io.StringIO(input_source) 10 | ls = input_source.split('\n') 11 | prev_toktype = token.INDENT 12 | readline = source.readline 13 | 14 | def get_char_index(lineno, col): 15 | # find the index of the char in the source code 16 | if lineno == 1: 17 | return len('\n'.join(ls[:(lineno-1)])) + col 18 | else: 19 | return len('\n'.join(ls[:(lineno-1)])) + col + 1 20 | 21 | def replace_char_between(start_lineno, start_col, end_lineno, end_col, source, replace_char, ls): 22 | # replace char between start_lineno, start_col and end_lineno, end_col with replace_char, but keep '\n' and ' ' 23 | b = get_char_index(start_lineno, start_col) 24 | e = get_char_index(end_lineno, end_col) 25 | for i in range(b, e): 26 | if source[i] == '\n': 27 | source = source[:i] + '\n' + source[i+1:] 28 | elif source[i] == ' ': 29 | source = source[:i] + ' ' + source[i+1:] 30 | else: 31 | source = source[:i] + replace_char + source[i+1:] 32 | return source 33 | 34 | tokgen = tokenize.generate_tokens(readline) 35 | for toktype, ttext, (slineno, scol), (elineno, ecol), ltext in tokgen: 36 | if toktype == token.STRING and (prev_toktype == token.INDENT): 37 | source_flag = replace_char_between(slineno, scol, elineno, ecol, source_flag, ' ', ls) 38 | elif toktype == token.STRING and (prev_toktype == token.NEWLINE): 39 | source_flag = replace_char_between(slineno, scol, elineno, ecol, source_flag, ' ', ls) 40 | elif toktype == tokenize.COMMENT: 41 | source_flag = replace_char_between(slineno, scol, elineno, ecol, source_flag, ' ', ls) 42 | prev_toktype = toktype 43 | return source_flag 44 | 45 | 46 | # 示例使用 47 | if __name__ == "__main__": 48 | with open("source.py", "r", encoding="utf-8") as f: 49 | source_code = f.read() 50 | 51 | cleaned_code = remove_python_comments(source_code) 52 | 53 | with open("cleaned_source.py", "w", encoding="utf-8") as f: 54 | f.write(cleaned_code) -------------------------------------------------------------------------------- /crazy_functions/doc_fns/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/binary-husky/gpt_academic/8c2143229113ad0953b4e4dfd2a543292ce65b14/crazy_functions/doc_fns/__init__.py -------------------------------------------------------------------------------- /crazy_functions/doc_fns/conversation_doc/markdown_doc.py: -------------------------------------------------------------------------------- 1 | 2 | class MarkdownFormatter: 3 | """Markdown格式文档生成器 - 用于生成对话记录的markdown文档""" 4 | 5 | def __init__(self): 6 | self.content = [] 7 | 8 | def _add_content(self, text: str): 9 | """添加正文内容""" 10 | if text: 11 | self.content.append(f"\n{text}\n") 12 | 13 | def create_document(self, history: list) -> str: 14 | """ 15 | 创建完整的Markdown文档 16 | Args: 17 | history: 历史记录列表，偶数位置为问题，奇数位置为答案 18 | Returns: 19 | str: 生成的Markdown文本 20 | """ 21 | self.content = [] 22 | 23 | # 处理问答对 24 | for i in range(0, len(history), 2): 25 | question = history[i] 26 | answer = history[i + 1] 27 | 28 | # 添加问题 29 | self.content.append(f"\n### 问题 {i//2 + 1}") 30 | self._add_content(question) 31 | 32 | # 添加回答 33 | self.content.append(f"\n### 回答 {i//2 + 1}") 34 | self._add_content(answer) 35 | 36 | # 添加分隔线 37 | self.content.append("\n---\n") 38 | 39 | return "\n".join(self.content) 40 | -------------------------------------------------------------------------------- /crazy_functions/doc_fns/conversation_doc/txt_doc.py: -------------------------------------------------------------------------------- 1 | 2 | import re 3 | 4 | 5 | def convert_markdown_to_txt(markdown_text): 6 | """Convert markdown text to plain text while preserving formatting""" 7 | # Standardize line endings 8 | markdown_text = markdown_text.replace('\r\n', '\n').replace('\r', '\n') 9 | 10 | # 1. Handle headers but keep their formatting instead of removing them 11 | markdown_text = re.sub(r'^#\s+(.+)$', r'# \1', markdown_text, flags=re.MULTILINE) 12 | markdown_text = re.sub(r'^##\s+(.+)$', r'## \1', markdown_text, flags=re.MULTILINE) 13 | markdown_text = re.sub(r'^###\s+(.+)$', r'### \1', markdown_text, flags=re.MULTILINE) 14 | 15 | # 2. Handle bold and italic - simply remove markers 16 | markdown_text = re.sub(r'\*\*(.+?)\*\*', r'\1', markdown_text) 17 | markdown_text = re.sub(r'\*(.+?)\*', r'\1', markdown_text) 18 | 19 | # 3. Handle lists but preserve formatting 20 | markdown_text = re.sub(r'^\s*[-*+]\s+(.+?)(?=\n|$)', r'• \1', markdown_text, flags=re.MULTILINE) 21 | 22 | # 4. Handle links - keep only the text 23 | markdown_text = re.sub(r'\[([^\]]+)\]\(([^)]+)\)', r'\1 (\2)', markdown_text) 24 | 25 | # 5. Handle HTML links - convert to user-friendly format 26 | markdown_text = re.sub(r'([^<]+)', r'\2 (\1)', 27 | markdown_text) 28 | 29 | # 6. Preserve paragraph breaks 30 | markdown_text = re.sub(r'\n{3,}', '\n\n', markdown_text) # normalize multiple newlines to double newlines 31 | 32 | # 7. Clean up extra spaces but maintain indentation 33 | markdown_text = re.sub(r' +', ' ', markdown_text) 34 | 35 | return markdown_text.strip() 36 | 37 | 38 | class TxtFormatter: 39 | """Chat history TXT document generator""" 40 | 41 | def __init__(self): 42 | self.content = [] 43 | self._setup_document() 44 | 45 | def _setup_document(self): 46 | """Initialize document with header""" 47 | self.content.append("=" * 50) 48 | self.content.append("GPT-Academic对话记录".center(48)) 49 | self.content.append("=" * 50) 50 | 51 | def _format_header(self): 52 | """Create document header with current date""" 53 | from datetime import datetime 54 | date_str = datetime.now().strftime('%Y年%m月%d日') 55 | return [ 56 | date_str.center(48), 57 | "\n" # Add blank line after date 58 | ] 59 | 60 | def create_document(self, history): 61 | """Generate document from chat history""" 62 | # Add header with date 63 | self.content.extend(self._format_header()) 64 | 65 | # Add conversation content 66 | for i in range(0, len(history), 2): 67 | question = history[i] 68 | answer = convert_markdown_to_txt(history[i + 1]) if i + 1 < len(history) else "" 69 | 70 | if question: 71 | self.content.append(f"问题 {i // 2 + 1}：{str(question)}") 72 | self.content.append("") # Add blank line 73 | 74 | if answer: 75 | self.content.append(f"回答 {i // 2 + 1}：{str(answer)}") 76 | self.content.append("") # Add blank line 77 | 78 | # Join all content with newlines 79 | return "\n".join(self.content) 80 | -------------------------------------------------------------------------------- /crazy_functions/doc_fns/read_fns/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/binary-husky/gpt_academic/8c2143229113ad0953b4e4dfd2a543292ce65b14/crazy_functions/doc_fns/read_fns/__init__.py -------------------------------------------------------------------------------- /crazy_functions/doc_fns/read_fns/docx_reader.py: -------------------------------------------------------------------------------- 1 | import nltk 2 | nltk.data.path.append('~/nltk_data') 3 | nltk.download('averaged_perceptron_tagger', download_dir='~/nltk_data', 4 | ) 5 | nltk.download('punkt', download_dir='~/nltk_data', 6 | ) -------------------------------------------------------------------------------- /crazy_functions/doc_fns/read_fns/unstructured_all/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/binary-husky/gpt_academic/8c2143229113ad0953b4e4dfd2a543292ce65b14/crazy_functions/doc_fns/read_fns/unstructured_all/__init__.py -------------------------------------------------------------------------------- /crazy_functions/doc_fns/read_fns/unstructured_all/unstructured_md.py: -------------------------------------------------------------------------------- 1 | from pathlib import Path 2 | from crazy_functions.doc_fns.read_fns.unstructured_all.paper_structure_extractor import PaperStructureExtractor 3 | 4 | def extract_and_save_as_markdown(paper_path, output_path=None): 5 | """ 6 | 提取论文结构并保存为Markdown格式 7 | 8 | 参数: 9 | paper_path: 论文文件路径 10 | output_path: 输出的Markdown文件路径，如果不指定，将使用与输入相同的文件名但扩展名为.md 11 | 12 | 返回: 13 | 保存的Markdown文件路径 14 | """ 15 | # 创建提取器 16 | extractor = PaperStructureExtractor() 17 | 18 | # 解析文件路径 19 | paper_path = Path(paper_path) 20 | 21 | # 如果未指定输出路径，使用相同文件名但扩展名为.md 22 | if output_path is None: 23 | output_path = paper_path.with_suffix('.md') 24 | else: 25 | output_path = Path(output_path) 26 | 27 | # 确保输出目录存在 28 | output_path.parent.mkdir(parents=True, exist_ok=True) 29 | 30 | print(f"正在处理论文: {paper_path}") 31 | 32 | try: 33 | # 提取论文结构 34 | paper = extractor.extract_paper_structure(paper_path) 35 | 36 | # 生成Markdown内容 37 | markdown_content = extractor.generate_markdown(paper) 38 | 39 | # 保存到文件 40 | with open(output_path, 'w', encoding='utf-8') as f: 41 | f.write(markdown_content) 42 | 43 | print(f"已成功保存Markdown文件: {output_path}") 44 | 45 | # 打印摘要信息 46 | print("\n论文摘要信息:") 47 | print(f"标题: {paper.metadata.title}") 48 | print(f"作者: {', '.join(paper.metadata.authors)}") 49 | print(f"关键词: {', '.join(paper.keywords)}") 50 | print(f"章节数: {len(paper.sections)}") 51 | print(f"图表数: {len(paper.figures)}") 52 | print(f"表格数: {len(paper.tables)}") 53 | print(f"公式数: {len(paper.formulas)}") 54 | print(f"参考文献数: {len(paper.references)}") 55 | 56 | return output_path 57 | 58 | except Exception as e: 59 | print(f"处理论文时出错: {e}") 60 | import traceback 61 | traceback.print_exc() 62 | return None 63 | 64 | # 使用示例 65 | if __name__ == "__main__": 66 | # 替换为实际的论文文件路径 67 | sample_paper = "crazy_functions/doc_fns/read_fns/paper/2501.12599v1.pdf" 68 | 69 | # 可以指定输出路径，也可以使用默认路径 70 | # output_file = "/path/to/output/paper_structure.md" 71 | # extract_and_save_as_markdown(sample_paper, output_file) 72 | 73 | # 使用默认输出路径（与输入文件同名但扩展名为.md） 74 | extract_and_save_as_markdown(sample_paper) 75 | 76 | # # 批量处理多个论文的示例 77 | # paper_dir = Path("/path/to/papers/folder") 78 | # output_dir = Path("/path/to/output/folder") 79 | # 80 | # # 确保输出目录存在 81 | # output_dir.mkdir(parents=True, exist_ok=True) 82 | # 83 | # # 处理目录中的所有PDF文件 84 | # for paper_file in paper_dir.glob("*.pdf"): 85 | # output_file = output_dir / f"{paper_file.stem}.md" 86 | # extract_and_save_as_markdown(paper_file, output_file) -------------------------------------------------------------------------------- /crazy_functions/game_fns/game_ascii_art.py: -------------------------------------------------------------------------------- 1 | from toolbox import CatchException, update_ui, update_ui_latest_msg 2 | from crazy_functions.multi_stage.multi_stage_utils import GptAcademicGameBaseState 3 | from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive 4 | from request_llms.bridge_all import predict_no_ui_long_connection 5 | from crazy_functions.game_fns.game_utils import get_code_block, is_same_thing 6 | import random 7 | 8 | 9 | class MiniGame_ASCII_Art(GptAcademicGameBaseState): 10 | def step(self, prompt, chatbot, history): 11 | if self.step_cnt == 0: 12 | chatbot.append(["我画你猜（动物）", "请稍等..."]) 13 | else: 14 | if prompt.strip() == 'exit': 15 | self.delete_game = True 16 | yield from update_ui_latest_msg(lastmsg=f"谜底是{self.obj}，游戏结束。", chatbot=chatbot, history=history, delay=0.) 17 | return 18 | chatbot.append([prompt, ""]) 19 | yield from update_ui(chatbot=chatbot, history=history) 20 | 21 | if self.step_cnt == 0: 22 | self.lock_plugin(chatbot) 23 | self.cur_task = 'draw' 24 | 25 | if self.cur_task == 'draw': 26 | avail_obj = ["狗","猫","鸟","鱼","老鼠","蛇"] 27 | self.obj = random.choice(avail_obj) 28 | inputs = "I want to play a game called Guess the ASCII art. You can draw the ASCII art and I will try to guess it. " + \ 29 | f"This time you draw a {self.obj}. Note that you must not indicate what you have draw in the text, and you should only produce the ASCII art wrapped by ```. " 30 | raw_res = predict_no_ui_long_connection(inputs=inputs, llm_kwargs=self.llm_kwargs, history=[], sys_prompt="") 31 | self.cur_task = 'identify user guess' 32 | res = get_code_block(raw_res) 33 | history += ['', f'the answer is {self.obj}', inputs, res] 34 | yield from update_ui_latest_msg(lastmsg=res, chatbot=chatbot, history=history, delay=0.) 35 | 36 | elif self.cur_task == 'identify user guess': 37 | if is_same_thing(self.obj, prompt, self.llm_kwargs): 38 | self.delete_game = True 39 | yield from update_ui_latest_msg(lastmsg="你猜对了！", chatbot=chatbot, history=history, delay=0.) 40 | else: 41 | self.cur_task = 'identify user guess' 42 | yield from update_ui_latest_msg(lastmsg="猜错了，再试试，输入“exit”获取答案。", chatbot=chatbot, history=history, delay=0.) -------------------------------------------------------------------------------- /crazy_functions/game_fns/game_utils.py: -------------------------------------------------------------------------------- 1 | 2 | from crazy_functions.json_fns.pydantic_io import GptJsonIO, JsonStringError 3 | from request_llms.bridge_all import predict_no_ui_long_connection 4 | def get_code_block(reply): 5 | import re 6 | pattern = r"```([\s\S]*?)```" # regex pattern to match code blocks 7 | matches = re.findall(pattern, reply) # find all code blocks in text 8 | if len(matches) == 1: 9 | return "```" + matches[0] + "```" # code block 10 | raise RuntimeError("GPT is not generating proper code.") 11 | 12 | def is_same_thing(a, b, llm_kwargs): 13 | from pydantic import BaseModel, Field 14 | class IsSameThing(BaseModel): 15 | is_same_thing: bool = Field(description="determine whether two objects are same thing.", default=False) 16 | 17 | def run_gpt_fn(inputs, sys_prompt, history=[]): 18 | return predict_no_ui_long_connection( 19 | inputs=inputs, llm_kwargs=llm_kwargs, 20 | history=history, sys_prompt=sys_prompt, observe_window=[] 21 | ) 22 | 23 | gpt_json_io = GptJsonIO(IsSameThing) 24 | inputs_01 = "Identity whether the user input and the target is the same thing: \n target object: {a} \n user input object: {b} \n\n\n".format(a=a, b=b) 25 | inputs_01 += "\n\n\n Note that the user may describe the target object with a different language, e.g. cat and 猫 are the same thing." 26 | analyze_res_cot_01 = run_gpt_fn(inputs_01, "", []) 27 | 28 | inputs_02 = inputs_01 + gpt_json_io.format_instructions 29 | analyze_res = run_gpt_fn(inputs_02, "", [inputs_01, analyze_res_cot_01]) 30 | 31 | try: 32 | res = gpt_json_io.generate_output_auto_repair(analyze_res, run_gpt_fn) 33 | return res.is_same_thing 34 | except JsonStringError as e: 35 | return False -------------------------------------------------------------------------------- /crazy_functions/gen_fns/gen_fns_shared.py: -------------------------------------------------------------------------------- 1 | import time 2 | import importlib 3 | from toolbox import trimmed_format_exc, gen_time_str, get_log_folder 4 | from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, is_the_upload_folder 5 | from toolbox import promote_file_to_downloadzone, get_log_folder, update_ui_latest_msg 6 | import multiprocessing 7 | 8 | def get_class_name(class_string): 9 | import re 10 | # Use regex to extract the class name 11 | class_name = re.search(r'class (\w+)\(', class_string).group(1) 12 | return class_name 13 | 14 | def try_make_module(code, chatbot): 15 | module_file = 'gpt_fn_' + gen_time_str().replace('-','_') 16 | fn_path = f'{get_log_folder(plugin_name="gen_plugin_verify")}/{module_file}.py' 17 | with open(fn_path, 'w', encoding='utf8') as f: f.write(code) 18 | promote_file_to_downloadzone(fn_path, chatbot=chatbot) 19 | class_name = get_class_name(code) 20 | manager = multiprocessing.Manager() 21 | return_dict = manager.dict() 22 | p = multiprocessing.Process(target=is_function_successfully_generated, args=(fn_path, class_name, return_dict)) 23 | # only has 10 seconds to run 24 | p.start(); p.join(timeout=10) 25 | if p.is_alive(): p.terminate(); p.join() 26 | p.close() 27 | return return_dict["success"], return_dict['traceback'] 28 | 29 | # check is_function_successfully_generated 30 | def is_function_successfully_generated(fn_path, class_name, return_dict): 31 | return_dict['success'] = False 32 | return_dict['traceback'] = "" 33 | try: 34 | # Create a spec for the module 35 | module_spec = importlib.util.spec_from_file_location('example_module', fn_path) 36 | # Load the module 37 | example_module = importlib.util.module_from_spec(module_spec) 38 | module_spec.loader.exec_module(example_module) 39 | # Now you can use the module 40 | some_class = getattr(example_module, class_name) 41 | # Now you can create an instance of the class 42 | instance = some_class() 43 | return_dict['success'] = True 44 | return 45 | except: 46 | return_dict['traceback'] = trimmed_format_exc() 47 | return 48 | 49 | def subprocess_worker(code, file_path, return_dict): 50 | return_dict['result'] = None 51 | return_dict['success'] = False 52 | return_dict['traceback'] = "" 53 | try: 54 | module_file = 'gpt_fn_' + gen_time_str().replace('-','_') 55 | fn_path = f'{get_log_folder(plugin_name="gen_plugin_run")}/{module_file}.py' 56 | with open(fn_path, 'w', encoding='utf8') as f: f.write(code) 57 | class_name = get_class_name(code) 58 | # Create a spec for the module 59 | module_spec = importlib.util.spec_from_file_location('example_module', fn_path) 60 | # Load the module 61 | example_module = importlib.util.module_from_spec(module_spec) 62 | module_spec.loader.exec_module(example_module) 63 | # Now you can use the module 64 | some_class = getattr(example_module, class_name) 65 | # Now you can create an instance of the class 66 | instance = some_class() 67 | return_dict['result'] = instance.run(file_path) 68 | return_dict['success'] = True 69 | except: 70 | return_dict['traceback'] = trimmed_format_exc() 71 | -------------------------------------------------------------------------------- /crazy_functions/ipc_fns/mp.py: -------------------------------------------------------------------------------- 1 | import platform 2 | import pickle 3 | import multiprocessing 4 | 5 | def run_in_subprocess_wrapper_func(v_args): 6 | func, args, kwargs, return_dict, exception_dict = pickle.loads(v_args) 7 | import sys 8 | try: 9 | result = func(*args, **kwargs) 10 | return_dict['result'] = result 11 | except Exception as e: 12 | exc_info = sys.exc_info() 13 | exception_dict['exception'] = exc_info 14 | 15 | def run_in_subprocess_with_timeout(func, timeout=60): 16 | if platform.system() == 'Linux': 17 | def wrapper(*args, **kwargs): 18 | return_dict = multiprocessing.Manager().dict() 19 | exception_dict = multiprocessing.Manager().dict() 20 | v_args = pickle.dumps((func, args, kwargs, return_dict, exception_dict)) 21 | process = multiprocessing.Process(target=run_in_subprocess_wrapper_func, args=(v_args,)) 22 | process.start() 23 | process.join(timeout) 24 | if process.is_alive(): 25 | process.terminate() 26 | raise TimeoutError(f'功能单元{str(func)}未能在规定时间内完成任务') 27 | process.close() 28 | if 'exception' in exception_dict: 29 | # ooops, the subprocess ran into an exception 30 | exc_info = exception_dict['exception'] 31 | raise exc_info[1].with_traceback(exc_info[2]) 32 | if 'result' in return_dict.keys(): 33 | # If the subprocess ran successfully, return the result 34 | return return_dict['result'] 35 | return wrapper 36 | else: 37 | return func -------------------------------------------------------------------------------- /crazy_functions/json_fns/select_tool.py: -------------------------------------------------------------------------------- 1 | from crazy_functions.json_fns.pydantic_io import GptJsonIO, JsonStringError 2 | 3 | def structure_output(txt, prompt, err_msg, run_gpt_fn, pydantic_cls): 4 | gpt_json_io = GptJsonIO(pydantic_cls) 5 | analyze_res = run_gpt_fn( 6 | txt, 7 | sys_prompt=prompt + gpt_json_io.format_instructions 8 | ) 9 | try: 10 | friend = gpt_json_io.generate_output_auto_repair(analyze_res, run_gpt_fn) 11 | except JsonStringError as e: 12 | return None, err_msg 13 | 14 | err_msg = "" 15 | return friend, err_msg 16 | 17 | 18 | def select_tool(prompt, run_gpt_fn, pydantic_cls): 19 | pydantic_cls_instance, err_msg = structure_output( 20 | txt=prompt, 21 | prompt="根据提示, 分析应该调用哪个工具函数\n\n", 22 | err_msg=f"不能理解该联系人", 23 | run_gpt_fn=run_gpt_fn, 24 | pydantic_cls=pydantic_cls 25 | ) 26 | return pydantic_cls_instance, err_msg -------------------------------------------------------------------------------- /crazy_functions/latex_fns/latex_pickle_io.py: -------------------------------------------------------------------------------- 1 | import pickle 2 | 3 | 4 | class SafeUnpickler(pickle.Unpickler): 5 | 6 | def get_safe_classes(self): 7 | from crazy_functions.latex_fns.latex_actions import LatexPaperFileGroup, LatexPaperSplit 8 | from crazy_functions.latex_fns.latex_toolbox import LinkedListNode 9 | from numpy.core.multiarray import scalar 10 | from numpy import dtype 11 | # 定义允许的安全类 12 | safe_classes = { 13 | # 在这里添加其他安全的类 14 | 'LatexPaperFileGroup': LatexPaperFileGroup, 15 | 'LatexPaperSplit': LatexPaperSplit, 16 | 'LinkedListNode': LinkedListNode, 17 | 'scalar': scalar, 18 | 'dtype': dtype, 19 | } 20 | return safe_classes 21 | 22 | def find_class(self, module, name): 23 | # 只允许特定的类进行反序列化 24 | self.safe_classes = self.get_safe_classes() 25 | match_class_name = None 26 | for class_name in self.safe_classes.keys(): 27 | if (class_name in f'{module}.{name}'): 28 | match_class_name = class_name 29 | if match_class_name is not None: 30 | return self.safe_classes[match_class_name] 31 | # 如果尝试加载未授权的类，则抛出异常 32 | raise pickle.UnpicklingError(f"Attempted to deserialize unauthorized class '{name}' from module '{module}'") 33 | 34 | def objdump(obj, file="objdump.tmp"): 35 | 36 | with open(file, "wb+") as f: 37 | pickle.dump(obj, f) 38 | return 39 | 40 | 41 | def objload(file="objdump.tmp"): 42 | import os 43 | 44 | if not os.path.exists(file): 45 | return 46 | with open(file, "rb") as f: 47 | unpickler = SafeUnpickler(f) 48 | return unpickler.load() 49 | -------------------------------------------------------------------------------- /crazy_functions/live_audio/audio_io.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | from scipy import interpolate 3 | 4 | def Singleton(cls): 5 | _instance = {} 6 | 7 | def _singleton(*args, **kargs): 8 | if cls not in _instance: 9 | _instance[cls] = cls(*args, **kargs) 10 | return _instance[cls] 11 | 12 | return _singleton 13 | 14 | 15 | @Singleton 16 | class RealtimeAudioDistribution(): 17 | def __init__(self) -> None: 18 | self.data = {} 19 | self.max_len = 1024*1024 20 | self.rate = 48000 # 只读，每秒采样数量 21 | 22 | def clean_up(self): 23 | self.data = {} 24 | 25 | def feed(self, uuid, audio): 26 | self.rate, audio_ = audio 27 | # print('feed', len(audio_), audio_[-25:]) 28 | if uuid not in self.data: 29 | self.data[uuid] = audio_ 30 | else: 31 | new_arr = np.concatenate((self.data[uuid], audio_)) 32 | if len(new_arr) > self.max_len: new_arr = new_arr[-self.max_len:] 33 | self.data[uuid] = new_arr 34 | 35 | def read(self, uuid): 36 | if uuid in self.data: 37 | res = self.data.pop(uuid) 38 | # print('\r read-', len(res), '-', max(res), end='', flush=True) 39 | else: 40 | res = None 41 | return res 42 | 43 | def change_sample_rate(audio, old_sr, new_sr): 44 | duration = audio.shape[0] / old_sr 45 | 46 | time_old = np.linspace(0, duration, audio.shape[0]) 47 | time_new = np.linspace(0, duration, int(audio.shape[0] * new_sr / old_sr)) 48 | 49 | interpolator = interpolate.interp1d(time_old, audio.T) 50 | new_audio = interpolator(time_new).T 51 | return new_audio.astype(np.int16) -------------------------------------------------------------------------------- /crazy_functions/media_fns/get_media.py: -------------------------------------------------------------------------------- 1 | from toolbox import update_ui, get_conf, promote_file_to_downloadzone, update_ui_latest_msg, generate_file_link 2 | from shared_utils.docker_as_service_api import stream_daas 3 | from shared_utils.docker_as_service_api import DockerServiceApiComModel 4 | import random 5 | 6 | def download_video(video_id, only_audio, user_name, chatbot, history): 7 | from toolbox import get_log_folder 8 | chatbot.append([None, "Processing..."]) 9 | yield from update_ui(chatbot, history) 10 | client_command = f'{video_id} --audio-only' if only_audio else video_id 11 | server_urls = get_conf('DAAS_SERVER_URLS') 12 | server_url = random.choice(server_urls) 13 | docker_service_api_com_model = DockerServiceApiComModel(client_command=client_command) 14 | save_file_dir = get_log_folder(user_name, plugin_name='media_downloader') 15 | for output_manifest in stream_daas(docker_service_api_com_model, server_url, save_file_dir): 16 | status_buf = "" 17 | status_buf += "DaaS message: \n\n" 18 | status_buf += output_manifest['server_message'].replace('\n', '
') 19 | status_buf += "\n\n" 20 | status_buf += "DaaS standard error: \n\n" 21 | status_buf += output_manifest['server_std_err'].replace('\n', '
') 22 | status_buf += "\n\n" 23 | status_buf += "DaaS standard output: \n\n" 24 | status_buf += output_manifest['server_std_out'].replace('\n', '
') 25 | status_buf += "\n\n" 26 | status_buf += "DaaS file attach: \n\n" 27 | status_buf += str(output_manifest['server_file_attach']) 28 | yield from update_ui_latest_msg(status_buf, chatbot, history) 29 | 30 | return output_manifest['server_file_attach'] 31 | 32 | 33 | def search_videos(keywords): 34 | from toolbox import get_log_folder 35 | client_command = keywords 36 | server_urls = get_conf('DAAS_SERVER_URLS') 37 | server_url = random.choice(server_urls) 38 | server_url = server_url.replace('stream', 'search') 39 | docker_service_api_com_model = DockerServiceApiComModel(client_command=client_command) 40 | save_file_dir = get_log_folder("default_user", plugin_name='media_downloader') 41 | for output_manifest in stream_daas(docker_service_api_com_model, server_url, save_file_dir): 42 | return output_manifest['server_message'] 43 | 44 | -------------------------------------------------------------------------------- /crazy_functions/pdf_fns/parse_pdf_grobid.py: -------------------------------------------------------------------------------- 1 | import os 2 | from toolbox import CatchException, report_exception, get_log_folder, gen_time_str, check_packages 3 | from toolbox import update_ui, promote_file_to_downloadzone, update_ui_latest_msg, disable_auto_promotion 4 | from toolbox import write_history_to_file, promote_file_to_downloadzone, get_conf, extract_archive 5 | from crazy_functions.pdf_fns.parse_pdf import parse_pdf, translate_pdf 6 | 7 | def 解析PDF_基于GROBID(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, grobid_url): 8 | import copy, json 9 | TOKEN_LIMIT_PER_FRAGMENT = 1024 10 | generated_conclusion_files = [] 11 | generated_html_files = [] 12 | DST_LANG = "中文" 13 | from crazy_functions.pdf_fns.report_gen_html import construct_html 14 | for index, fp in enumerate(file_manifest): 15 | chatbot.append(["当前进度：", f"正在连接GROBID服务，请稍候: {grobid_url}\n如果等待时间过长，请修改config中的GROBID_URL，可修改成本地GROBID服务。"]); yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 16 | article_dict = parse_pdf(fp, grobid_url) 17 | grobid_json_res = os.path.join(get_log_folder(), gen_time_str() + "grobid.json") 18 | with open(grobid_json_res, 'w+', encoding='utf8') as f: 19 | f.write(json.dumps(article_dict, indent=4, ensure_ascii=False)) 20 | promote_file_to_downloadzone(grobid_json_res, chatbot=chatbot) 21 | if article_dict is None: raise RuntimeError("解析PDF失败，请检查PDF是否损坏。") 22 | yield from translate_pdf(article_dict, llm_kwargs, chatbot, fp, generated_conclusion_files, TOKEN_LIMIT_PER_FRAGMENT, DST_LANG, plugin_kwargs=plugin_kwargs) 23 | chatbot.append(("给出输出文件清单", str(generated_conclusion_files + generated_html_files))) 24 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 25 | 26 | 27 | -------------------------------------------------------------------------------- /crazy_functions/pdf_fns/report_gen_html.py: -------------------------------------------------------------------------------- 1 | from toolbox import update_ui, get_conf, trimmed_format_exc, get_log_folder 2 | import os 3 | 4 | 5 | 6 | 7 | class construct_html(): 8 | def __init__(self) -> None: 9 | self.html_string = "" 10 | 11 | def add_row(self, a, b): 12 | from toolbox import markdown_convertion 13 | template = """ 14 | { 15 | primary_col: { 16 | header: String.raw`__PRIMARY_HEADER__`, 17 | msg: String.raw`__PRIMARY_MSG__`, 18 | }, 19 | secondary_rol: { 20 | header: String.raw`__SECONDARY_HEADER__`, 21 | msg: String.raw`__SECONDARY_MSG__`, 22 | } 23 | }, 24 | """ 25 | def std(str): 26 | str = str.replace(r'`',r'`') 27 | if str.endswith("\\"): str += ' ' 28 | if str.endswith("}"): str += ' ' 29 | if str.endswith("$"): str += ' ' 30 | return str 31 | 32 | template_ = template 33 | a_lines = a.split('\n') 34 | b_lines = b.split('\n') 35 | 36 | if len(a_lines) == 1 or len(a_lines[0]) > 50: 37 | template_ = template_.replace("__PRIMARY_HEADER__", std(a[:20])) 38 | template_ = template_.replace("__PRIMARY_MSG__", std(markdown_convertion(a))) 39 | else: 40 | template_ = template_.replace("__PRIMARY_HEADER__", std(a_lines[0])) 41 | template_ = template_.replace("__PRIMARY_MSG__", std(markdown_convertion('\n'.join(a_lines[1:])))) 42 | 43 | if len(b_lines) == 1 or len(b_lines[0]) > 50: 44 | template_ = template_.replace("__SECONDARY_HEADER__", std(b[:20])) 45 | template_ = template_.replace("__SECONDARY_MSG__", std(markdown_convertion(b))) 46 | else: 47 | template_ = template_.replace("__SECONDARY_HEADER__", std(b_lines[0])) 48 | template_ = template_.replace("__SECONDARY_MSG__", std(markdown_convertion('\n'.join(b_lines[1:])))) 49 | self.html_string += template_ 50 | 51 | def save_file(self, file_name): 52 | from toolbox import get_log_folder 53 | with open('crazy_functions/pdf_fns/report_template.html', 'r', encoding='utf8') as f: 54 | html_template = f.read() 55 | html_template = html_template.replace("__TF_ARR__", self.html_string) 56 | with open(os.path.join(get_log_folder(), file_name), 'w', encoding='utf8') as f: 57 | f.write(html_template.encode('utf-8', 'ignore').decode()) 58 | return os.path.join(get_log_folder(), file_name) 59 | -------------------------------------------------------------------------------- /crazy_functions/pdf_fns/report_template_v2.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | GPT-Academic 翻译报告书 7 | 29 | 41 | 42 | 43 | 47 | 48 | 49 | 50 | 51 |
52 | 53 |
54 |
55 | 56 |
57 | 请按Ctrl+S保存此页面，否则该页面可能在几分钟后失效。 58 |
59 | 60 | 61 |
62 | 本报告由GPT-Academic开源项目生成，地址：https://github.com/binary-husky/gpt_academic。 63 |
64 |
65 | 本报告由GPT-Academic开源项目生成，地址：https://github.com/binary-husky/gpt_academic。 66 |
67 |
68 |
69 |
70 | 71 | 72 | 73 | -------------------------------------------------------------------------------- /crazy_functions/plugin_template/plugin_class_template.py: -------------------------------------------------------------------------------- 1 | import os, json, base64 2 | from pydantic import BaseModel, Field 3 | from textwrap import dedent 4 | from typing import List 5 | 6 | class ArgProperty(BaseModel): # PLUGIN_ARG_MENU 7 | title: str = Field(description="The title", default="") 8 | description: str = Field(description="The description", default="") 9 | default_value: str = Field(description="The default value", default="") 10 | type: str = Field(description="The type", default="") # currently we support ['string', 'dropdown'] 11 | options: List[str] = Field(default=[], description="List of options available for the argument") # only used when type is 'dropdown' 12 | 13 | class GptAcademicPluginTemplate(): 14 | def __init__(self): 15 | # please note that `execute` method may run in different threads, 16 | # thus you should not store any state in the plugin instance, 17 | # which may be accessed by multiple threads 18 | pass 19 | 20 | 21 | def define_arg_selection_menu(self): 22 | """ 23 | An example as below: 24 | ``` 25 | def define_arg_selection_menu(self): 26 | gui_definition = { 27 | "main_input": 28 | ArgProperty(title="main input", description="description", default_value="default_value", type="string").model_dump_json(), 29 | "advanced_arg": 30 | ArgProperty(title="advanced arguments", description="description", default_value="default_value", type="string").model_dump_json(), 31 | "additional_arg_01": 32 | ArgProperty(title="additional", description="description", default_value="default_value", type="string").model_dump_json(), 33 | } 34 | return gui_definition 35 | ``` 36 | """ 37 | raise NotImplementedError("You need to implement this method in your plugin class") 38 | 39 | 40 | def get_js_code_for_generating_menu(self, btnName): 41 | define_arg_selection = self.define_arg_selection_menu() 42 | 43 | if len(define_arg_selection.keys()) > 8: 44 | raise ValueError("You can only have up to 8 arguments in the define_arg_selection") 45 | # if "main_input" not in define_arg_selection: 46 | # raise ValueError("You must have a 'main_input' in the define_arg_selection") 47 | 48 | DEFINE_ARG_INPUT_INTERFACE = json.dumps(define_arg_selection) 49 | return base64.b64encode(DEFINE_ARG_INPUT_INTERFACE.encode('utf-8')).decode('utf-8') 50 | 51 | def execute(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request): 52 | raise NotImplementedError("You need to implement this method in your plugin class") -------------------------------------------------------------------------------- /crazy_functions/prompts/internet.py: -------------------------------------------------------------------------------- 1 | SearchOptimizerPrompt="""作为一个网页搜索助手，你的任务是结合历史记录，从不同角度，为“原问题”生成个不同版本的“检索词”，从而提高网页检索的精度。生成的问题要求指向对象清晰明确，并与“原问题语言相同”。例如： 2 | 历史记录: 3 | " 4 | Q: 对话背景。 5 | A: 当前对话是关于 Nginx 的介绍和在Ubuntu上的使用等。 6 | " 7 | 原问题: 怎么下载 8 | 检索词: ["Nginx 下载","Ubuntu Nginx","Ubuntu安装Nginx"] 9 | ---------------- 10 | 历史记录: 11 | " 12 | Q: 对话背景。 13 | A: 当前对话是关于 Nginx 的介绍和使用等。 14 | Q: 报错 "no connection" 15 | A: 报错"no connection"可能是因为…… 16 | " 17 | 原问题: 怎么解决 18 | 检索词: ["Nginx报错"no connection" 解决","Nginx'no connection'报错 原因","Nginx提示'no connection'"] 19 | ---------------- 20 | 历史记录: 21 | " 22 | 23 | " 24 | 原问题: 你知道 Python 么？ 25 | 检索词: ["Python","Python 使用教程。","Python 特点和优势"] 26 | ---------------- 27 | 历史记录: 28 | " 29 | Q: 列出Java的三种特点？ 30 | A: 1. Java 是一种编译型语言。 31 | 2. Java 是一种面向对象的编程语言。 32 | 3. Java 是一种跨平台的编程语言。 33 | " 34 | 原问题: 介绍下第2点。 35 | 检索词: ["Java 面向对象特点","Java 面向对象编程优势。","Java 面向对象编程"] 36 | ---------------- 37 | 现在有历史记录: 38 | " 39 | {history} 40 | " 41 | 有其原问题: {query} 42 | 直接给出最多{num}个检索词，必须以json形式给出，不得有多余字符: 43 | """ 44 | 45 | SearchAcademicOptimizerPrompt="""作为一个学术论文搜索助手，你的任务是结合历史记录，从不同角度，为“原问题”生成个不同版本的“检索词”，从而提高学术论文检索的精度。生成的问题要求指向对象清晰明确，并与“原问题语言相同”。例如： 46 | 历史记录: 47 | " 48 | Q: 对话背景。 49 | A: 当前对话是关于深度学习的介绍和在图像识别中的应用等。 50 | " 51 | 原问题: 怎么下载相关论文 52 | 检索词: ["深度学习 图像识别 论文下载","图像识别 深度学习 研究论文","深度学习 图像识别 论文资源","Deep Learning Image Recognition Paper Download","Image Recognition Deep Learning Research Paper"] 53 | ---------------- 54 | 历史记录: 55 | " 56 | Q: 对话背景。 57 | A: 当前对话是关于深度学习的介绍和应用等。 58 | Q: 报错 "模型不收敛" 59 | A: 报错"模型不收敛"可能是因为…… 60 | " 61 | 原问题: 怎么解决 62 | 检索词: ["深度学习 模型不收敛 解决方案 论文","深度学习 模型不收敛 原因 研究","深度学习 模型不收敛 论文","Deep Learning Model Convergence Issue Solution Paper","Deep Learning Model Convergence Problem Research"] 63 | ---------------- 64 | 历史记录: 65 | " 66 | 67 | " 68 | 原问题: 你知道 GAN 么？ 69 | 检索词: ["生成对抗网络 论文","GAN 使用教程 论文","GAN 特点和优势 研究","Generative Adversarial Network Paper","GAN Usage Tutorial Paper"] 70 | ---------------- 71 | 历史记录: 72 | " 73 | Q: 列出机器学习的三种应用？ 74 | A: 1. 机器学习在图像识别中的应用。 75 | 2. 机器学习在自然语言处理中的应用。 76 | 3. 机器学习在推荐系统中的应用。 77 | " 78 | 原问题: 介绍下第2点。 79 | 检索词: ["机器学习 自然语言处理 应用 论文","机器学习 自然语言处理 研究","机器学习 NLP 应用 论文","Machine Learning Natural Language Processing Application Paper","Machine Learning NLP Research"] 80 | ---------------- 81 | 现在有历史记录: 82 | " 83 | {history} 84 | " 85 | 有其原问题: {query} 86 | 直接给出最多{num}个检索词，必须以json形式给出，不得有多余字符: 87 | """ -------------------------------------------------------------------------------- /crazy_functions/rag_fns/rag_file_support.py: -------------------------------------------------------------------------------- 1 | import os 2 | from llama_index.core import SimpleDirectoryReader 3 | 4 | supports_format = ['.csv', '.docx', '.epub', '.ipynb', '.mbox', '.md', '.pdf', '.txt', '.ppt', 5 | '.pptm', '.pptx'] 6 | 7 | 8 | # 修改后的 extract_text 函数，结合 SimpleDirectoryReader 和自定义解析逻辑 9 | def extract_text(file_path): 10 | _, ext = os.path.splitext(file_path.lower()) 11 | 12 | # 使用 SimpleDirectoryReader 处理它支持的文件格式 13 | if ext in supports_format: 14 | try: 15 | reader = SimpleDirectoryReader(input_files=[file_path]) 16 | documents = reader.load_data() 17 | if len(documents) > 0: 18 | return documents[0].text 19 | except Exception as e: 20 | pass 21 | 22 | return None 23 | -------------------------------------------------------------------------------- /crazy_functions/rag_fns/vector_store_index.py: -------------------------------------------------------------------------------- 1 | from llama_index.core import VectorStoreIndex 2 | from typing import Any, List, Optional 3 | 4 | from llama_index.core.callbacks.base import CallbackManager 5 | from llama_index.core.schema import TransformComponent 6 | from llama_index.core.service_context import ServiceContext 7 | from llama_index.core.settings import ( 8 | Settings, 9 | callback_manager_from_settings_or_context, 10 | transformations_from_settings_or_context, 11 | ) 12 | from llama_index.core.storage.storage_context import StorageContext 13 | 14 | 15 | class GptacVectorStoreIndex(VectorStoreIndex): 16 | 17 | @classmethod 18 | def default_vector_store( 19 | cls, 20 | storage_context: Optional[StorageContext] = None, 21 | show_progress: bool = False, 22 | callback_manager: Optional[CallbackManager] = None, 23 | transformations: Optional[List[TransformComponent]] = None, 24 | # deprecated 25 | service_context: Optional[ServiceContext] = None, 26 | embed_model = None, 27 | **kwargs: Any, 28 | ): 29 | """Create index from documents. 30 | 31 | Args: 32 | documents (Optional[Sequence[BaseDocument]]): List of documents to 33 | build the index from. 34 | 35 | """ 36 | storage_context = storage_context or StorageContext.from_defaults() 37 | docstore = storage_context.docstore 38 | callback_manager = ( 39 | callback_manager 40 | or callback_manager_from_settings_or_context(Settings, service_context) 41 | ) 42 | transformations = transformations or transformations_from_settings_or_context( 43 | Settings, service_context 44 | ) 45 | 46 | with callback_manager.as_trace("index_construction"): 47 | 48 | return cls( 49 | nodes=[], 50 | storage_context=storage_context, 51 | callback_manager=callback_manager, 52 | show_progress=show_progress, 53 | transformations=transformations, 54 | service_context=service_context, 55 | embed_model=embed_model, 56 | **kwargs, 57 | ) 58 | 59 | -------------------------------------------------------------------------------- /crazy_functions/vector_fns/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/binary-husky/gpt_academic/8c2143229113ad0953b4e4dfd2a543292ce65b14/crazy_functions/vector_fns/__init__.py -------------------------------------------------------------------------------- /crazy_functions/vector_fns/general_file_loader.py: -------------------------------------------------------------------------------- 1 | # From project chatglm-langchain 2 | 3 | 4 | from langchain.document_loaders import UnstructuredFileLoader 5 | from langchain.text_splitter import CharacterTextSplitter 6 | import re 7 | from typing import List 8 | 9 | class ChineseTextSplitter(CharacterTextSplitter): 10 | def __init__(self, pdf: bool = False, sentence_size: int = None, **kwargs): 11 | super().__init__(**kwargs) 12 | self.pdf = pdf 13 | self.sentence_size = sentence_size 14 | 15 | def split_text1(self, text: str) -> List[str]: 16 | if self.pdf: 17 | text = re.sub(r"\n{3,}", "\n", text) 18 | text = re.sub('\s', ' ', text) 19 | text = text.replace("\n\n", "") 20 | sent_sep_pattern = re.compile('([﹒﹔﹖﹗．。！？]["’”」』]{0,2}|(?=["‘“「『]{1,2}|$))') # del ：； 21 | sent_list = [] 22 | for ele in sent_sep_pattern.split(text): 23 | if sent_sep_pattern.match(ele) and sent_list: 24 | sent_list[-1] += ele 25 | elif ele: 26 | sent_list.append(ele) 27 | return sent_list 28 | 29 | def split_text(self, text: str) -> List[str]: ##此处需要进一步优化逻辑 30 | if self.pdf: 31 | text = re.sub(r"\n{3,}", r"\n", text) 32 | text = re.sub('\s', " ", text) 33 | text = re.sub("\n\n", "", text) 34 | 35 | text = re.sub(r'([;；.!?。！？\?])([^”’])', r"\1\n\2", text) # 单字符断句符 36 | text = re.sub(r'(\.{6})([^"’”」』])', r"\1\n\2", text) # 英文省略号 37 | text = re.sub(r'(\…{2})([^"’”」』])', r"\1\n\2", text) # 中文省略号 38 | text = re.sub(r'([;；!?。！？\?]["’”」』]{0,2})([^;；!?，。！？\?])', r'\1\n\2', text) 39 | # 如果双引号前有终止符，那么双引号才是句子的终点，把分句符\n放到双引号后，注意前面的几句都小心保留了双引号 40 | text = text.rstrip() # 段尾如果有多余的\n就去掉它 41 | # 很多规则中会考虑分号;，但是这里我把它忽略不计，破折号、英文双引号等同样忽略，需要的再做些简单调整即可。 42 | ls = [i for i in text.split("\n") if i] 43 | for ele in ls: 44 | if len(ele) > self.sentence_size: 45 | ele1 = re.sub(r'([,，.]["’”」』]{0,2})([^,，.])', r'\1\n\2', ele) 46 | ele1_ls = ele1.split("\n") 47 | for ele_ele1 in ele1_ls: 48 | if len(ele_ele1) > self.sentence_size: 49 | ele_ele2 = re.sub(r'([\n]{1,}| {2,}["’”」』]{0,2})([^\s])', r'\1\n\2', ele_ele1) 50 | ele2_ls = ele_ele2.split("\n") 51 | for ele_ele2 in ele2_ls: 52 | if len(ele_ele2) > self.sentence_size: 53 | ele_ele3 = re.sub('( ["’”」』]{0,2})([^ ])', r'\1\n\2', ele_ele2) 54 | ele2_id = ele2_ls.index(ele_ele2) 55 | ele2_ls = ele2_ls[:ele2_id] + [i for i in ele_ele3.split("\n") if i] + ele2_ls[ 56 | ele2_id + 1:] 57 | ele_id = ele1_ls.index(ele_ele1) 58 | ele1_ls = ele1_ls[:ele_id] + [i for i in ele2_ls if i] + ele1_ls[ele_id + 1:] 59 | 60 | id = ls.index(ele) 61 | ls = ls[:id] + [i for i in ele1_ls if i] + ls[id + 1:] 62 | return ls 63 | 64 | def load_file(filepath, sentence_size): 65 | loader = UnstructuredFileLoader(filepath, mode="elements") 66 | textsplitter = ChineseTextSplitter(pdf=False, sentence_size=sentence_size) 67 | docs = loader.load_and_split(text_splitter=textsplitter) 68 | # write_check_file(filepath, docs) 69 | return docs 70 | 71 | -------------------------------------------------------------------------------- /crazy_functions/vt_fns/vt_state.py: -------------------------------------------------------------------------------- 1 | import pickle 2 | 3 | class VoidTerminalState(): 4 | def __init__(self): 5 | self.reset_state() 6 | 7 | def reset_state(self): 8 | self.has_provided_explanation = False 9 | 10 | def lock_plugin(self, chatbot): 11 | chatbot._cookies['lock_plugin'] = 'crazy_functions.虚空终端->虚空终端' 12 | chatbot._cookies['plugin_state'] = pickle.dumps(self) 13 | 14 | def unlock_plugin(self, chatbot): 15 | self.reset_state() 16 | chatbot._cookies['lock_plugin'] = None 17 | chatbot._cookies['plugin_state'] = pickle.dumps(self) 18 | 19 | def set_state(self, chatbot, key, value): 20 | setattr(self, key, value) 21 | chatbot._cookies['plugin_state'] = pickle.dumps(self) 22 | 23 | def get_state(chatbot): 24 | state = chatbot._cookies.get('plugin_state', None) 25 | if state is not None: state = pickle.loads(state) 26 | else: state = VoidTerminalState() 27 | state.chatbot = chatbot 28 | return state -------------------------------------------------------------------------------- /crazy_functions/互动小游戏.py: -------------------------------------------------------------------------------- 1 | from toolbox import CatchException, update_ui, update_ui_latest_msg 2 | from crazy_functions.multi_stage.multi_stage_utils import GptAcademicGameBaseState 3 | from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive 4 | from request_llms.bridge_all import predict_no_ui_long_connection 5 | from crazy_functions.game_fns.game_utils import get_code_block, is_same_thing 6 | 7 | @CatchException 8 | def 随机小游戏(prompt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request): 9 | from crazy_functions.game_fns.game_interactive_story import MiniGame_ResumeStory 10 | # 清空历史 11 | history = [] 12 | # 选择游戏 13 | cls = MiniGame_ResumeStory 14 | # 如果之前已经初始化了游戏实例，则继续该实例；否则重新初始化 15 | state = cls.sync_state(chatbot, 16 | llm_kwargs, 17 | cls, 18 | plugin_name='MiniGame_ResumeStory', 19 | callback_fn='crazy_functions.互动小游戏->随机小游戏', 20 | lock_plugin=True 21 | ) 22 | yield from state.continue_game(prompt, chatbot, history) 23 | 24 | 25 | @CatchException 26 | def 随机小游戏1(prompt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request): 27 | from crazy_functions.game_fns.game_ascii_art import MiniGame_ASCII_Art 28 | # 清空历史 29 | history = [] 30 | # 选择游戏 31 | cls = MiniGame_ASCII_Art 32 | # 如果之前已经初始化了游戏实例，则继续该实例；否则重新初始化 33 | state = cls.sync_state(chatbot, 34 | llm_kwargs, 35 | cls, 36 | plugin_name='MiniGame_ASCII_Art', 37 | callback_fn='crazy_functions.互动小游戏->随机小游戏1', 38 | lock_plugin=True 39 | ) 40 | yield from state.continue_game(prompt, chatbot, history) 41 | -------------------------------------------------------------------------------- /crazy_functions/交互功能函数模板.py: -------------------------------------------------------------------------------- 1 | from toolbox import CatchException, update_ui 2 | from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive 3 | 4 | @CatchException 5 | def 交互功能模板函数(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request): 6 | """ 7 | txt 输入栏用户输入的文本，例如需要翻译的一段话，再例如一个包含了待处理文件的路径 8 | llm_kwargs gpt模型参数, 如温度和top_p等, 一般原样传递下去就行 9 | plugin_kwargs 插件模型的参数, 如温度和top_p等, 一般原样传递下去就行 10 | chatbot 聊天显示框的句柄，用于显示给用户 11 | history 聊天历史，前情提要 12 | system_prompt 给gpt的静默提醒 13 | user_request 当前用户的请求信息（IP地址等） 14 | """ 15 | history = [] # 清空历史，以免输入溢出 16 | chatbot.append(("这是什么功能？", "交互功能函数模板。在执行完成之后, 可以将自身的状态存储到cookie中, 等待用户的再次调用。")) 17 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 18 | 19 | state = chatbot._cookies.get('plugin_state_0001', None) # 初始化插件状态 20 | 21 | if state is None: 22 | chatbot._cookies['lock_plugin'] = 'crazy_functions.交互功能函数模板->交互功能模板函数' # 赋予插件锁定 锁定插件回调路径，当下一次用户提交时，会直接转到该函数 23 | chatbot._cookies['plugin_state_0001'] = 'wait_user_keyword' # 赋予插件状态 24 | 25 | chatbot.append(("第一次调用：", "请输入关键词, 我将为您查找相关壁纸, 建议使用英文单词, 插件锁定中，请直接提交即可。")) 26 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 27 | return 28 | 29 | if state == 'wait_user_keyword': 30 | chatbot._cookies['lock_plugin'] = None # 解除插件锁定，避免遗忘导致死锁 31 | chatbot._cookies['plugin_state_0001'] = None # 解除插件状态，避免遗忘导致死锁 32 | 33 | # 解除插件锁定 34 | chatbot.append((f"获取关键词：{txt}", "")) 35 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 36 | page_return = get_image_page_by_keyword(txt) 37 | inputs=inputs_show_user=f"Extract all image urls in this html page, pick the first 5 images and show them with markdown format: \n\n {page_return}" 38 | gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive( 39 | inputs=inputs, inputs_show_user=inputs_show_user, 40 | llm_kwargs=llm_kwargs, chatbot=chatbot, history=[], 41 | sys_prompt="When you want to show an image, use markdown format. e.g. ![image_description](image_url). If there are no image url provided, answer 'no image url provided'" 42 | ) 43 | chatbot[-1] = [chatbot[-1][0], gpt_say] 44 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 45 | return 46 | 47 | 48 | 49 | # --------------------------------------------------------------------------------- 50 | 51 | def get_image_page_by_keyword(keyword): 52 | import requests 53 | from bs4 import BeautifulSoup 54 | response = requests.get(f'https://wallhaven.cc/search?q={keyword}', timeout=2) 55 | res = "image urls: \n" 56 | for image_element in BeautifulSoup(response.content, 'html.parser').findAll("img"): 57 | try: 58 | res += image_element["data-src"] 59 | res += "\n" 60 | except: 61 | pass 62 | return res 63 | -------------------------------------------------------------------------------- /crazy_functions/命令行助手.py: -------------------------------------------------------------------------------- 1 | from toolbox import CatchException, update_ui, gen_time_str 2 | from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive 3 | from crazy_functions.crazy_utils import input_clipping 4 | import copy, json 5 | 6 | @CatchException 7 | def 命令行助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request): 8 | """ 9 | txt 输入栏用户输入的文本, 例如需要翻译的一段话, 再例如一个包含了待处理文件的路径 10 | llm_kwargs gpt模型参数, 如温度和top_p等, 一般原样传递下去就行 11 | plugin_kwargs 插件模型的参数, 暂时没有用武之地 12 | chatbot 聊天显示框的句柄, 用于显示给用户 13 | history 聊天历史, 前情提要 14 | system_prompt 给gpt的静默提醒 15 | user_request 当前用户的请求信息（IP地址等） 16 | """ 17 | # 清空历史, 以免输入溢出 18 | history = [] 19 | 20 | # 输入 21 | i_say = "请写bash命令实现以下功能：" + txt 22 | # 开始 23 | gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive( 24 | inputs=i_say, inputs_show_user=txt, 25 | llm_kwargs=llm_kwargs, chatbot=chatbot, history=[], 26 | sys_prompt="你是一个Linux大师级用户。注意，当我要求你写bash命令时，尽可能地仅用一行命令解决我的要求。" 27 | ) 28 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新 29 | 30 | 31 | 32 | -------------------------------------------------------------------------------- /crazy_functions/生成函数注释.py: -------------------------------------------------------------------------------- 1 | from loguru import logger 2 | from toolbox import update_ui 3 | from toolbox import CatchException, report_exception 4 | from toolbox import write_history_to_file, promote_file_to_downloadzone 5 | from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive 6 | 7 | def 生成函数注释(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt): 8 | import time, os 9 | logger.info('begin analysis on:', file_manifest) 10 | for index, fp in enumerate(file_manifest): 11 | with open(fp, 'r', encoding='utf-8', errors='replace') as f: 12 | file_content = f.read() 13 | 14 | i_say = f'请对下面的程序文件做一个概述，并对文件中的所有函数生成注释，使用markdown表格输出结果，文件名是{os.path.relpath(fp, project_folder)}，文件内容是 ```{file_content}```' 15 | i_say_show_user = f'[{index+1}/{len(file_manifest)}] 请对下面的程序文件做一个概述，并对文件中的所有函数生成注释: {os.path.abspath(fp)}' 16 | chatbot.append((i_say_show_user, "[Local Message] waiting gpt response.")) 17 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 18 | 19 | msg = '正常' 20 | # ** gpt request ** 21 | gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive( 22 | i_say, i_say_show_user, llm_kwargs, chatbot, history=[], sys_prompt=system_prompt) # 带超时倒计时 23 | 24 | chatbot[-1] = (i_say_show_user, gpt_say) 25 | history.append(i_say_show_user); history.append(gpt_say) 26 | yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面 27 | time.sleep(2) 28 | 29 | res = write_history_to_file(history) 30 | promote_file_to_downloadzone(res, chatbot=chatbot) 31 | chatbot.append(("完成了吗？", res)) 32 | yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面 33 | 34 | 35 | 36 | @CatchException 37 | def 批量生成函数注释(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request): 38 | history = [] # 清空历史，以免输入溢出 39 | import glob, os 40 | if os.path.exists(txt): 41 | project_folder = txt 42 | else: 43 | if txt == "": txt = '空空如也的输入栏' 44 | report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}") 45 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 46 | return 47 | file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.py', recursive=True)] + \ 48 | [f for f in glob.glob(f'{project_folder}/**/*.cpp', recursive=True)] 49 | 50 | if len(file_manifest) == 0: 51 | report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex文件: {txt}") 52 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 53 | return 54 | yield from 生成函数注释(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt) 55 | -------------------------------------------------------------------------------- /crazy_functions/询问多个大语言模型.py: -------------------------------------------------------------------------------- 1 | from toolbox import CatchException, update_ui, get_conf 2 | from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive 3 | import datetime 4 | @CatchException 5 | def 同时问询(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request): 6 | """ 7 | txt 输入栏用户输入的文本，例如需要翻译的一段话，再例如一个包含了待处理文件的路径 8 | llm_kwargs gpt模型参数，如温度和top_p等，一般原样传递下去就行 9 | plugin_kwargs 插件模型的参数，用于灵活调整复杂功能的各种参数 10 | chatbot 聊天显示框的句柄，用于显示给用户 11 | history 聊天历史，前情提要 12 | system_prompt 给gpt的静默提醒 13 | user_request 当前用户的请求信息（IP地址等） 14 | """ 15 | history = [] # 清空历史，以免输入溢出 16 | MULTI_QUERY_LLM_MODELS = get_conf('MULTI_QUERY_LLM_MODELS') 17 | chatbot.append((txt, "正在同时咨询" + MULTI_QUERY_LLM_MODELS)) 18 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 由于请求gpt需要一段时间，我们先及时地做一次界面更新 19 | 20 | # llm_kwargs['llm_model'] = 'chatglm&gpt-3.5-turbo&api2d-gpt-3.5-turbo' # 支持任意数量的llm接口，用&符号分隔 21 | llm_kwargs['llm_model'] = MULTI_QUERY_LLM_MODELS # 支持任意数量的llm接口，用&符号分隔 22 | gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive( 23 | inputs=txt, inputs_show_user=txt, 24 | llm_kwargs=llm_kwargs, chatbot=chatbot, history=history, 25 | sys_prompt=system_prompt, 26 | retry_times_at_unknown_error=0 27 | ) 28 | 29 | history.append(txt) 30 | history.append(gpt_say) 31 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新 32 | 33 | 34 | @CatchException 35 | def 同时问询_指定模型(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request): 36 | """ 37 | txt 输入栏用户输入的文本，例如需要翻译的一段话，再例如一个包含了待处理文件的路径 38 | llm_kwargs gpt模型参数，如温度和top_p等，一般原样传递下去就行 39 | plugin_kwargs 插件模型的参数，用于灵活调整复杂功能的各种参数 40 | chatbot 聊天显示框的句柄，用于显示给用户 41 | history 聊天历史，前情提要 42 | system_prompt 给gpt的静默提醒 43 | user_request 当前用户的请求信息（IP地址等） 44 | """ 45 | history = [] # 清空历史，以免输入溢出 46 | 47 | if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg") 48 | # llm_kwargs['llm_model'] = 'chatglm&gpt-3.5-turbo&api2d-gpt-3.5-turbo' # 支持任意数量的llm接口，用&符号分隔 49 | llm_kwargs['llm_model'] = plugin_kwargs.get("advanced_arg", 'chatglm&gpt-3.5-turbo') # 'chatglm&gpt-3.5-turbo' # 支持任意数量的llm接口，用&符号分隔 50 | 51 | chatbot.append((txt, f"正在同时咨询{llm_kwargs['llm_model']}")) 52 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 由于请求gpt需要一段时间，我们先及时地做一次界面更新 53 | 54 | gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive( 55 | inputs=txt, inputs_show_user=txt, 56 | llm_kwargs=llm_kwargs, chatbot=chatbot, history=history, 57 | sys_prompt=system_prompt, 58 | retry_times_at_unknown_error=0 59 | ) 60 | 61 | history.append(txt) 62 | history.append(gpt_say) 63 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新 -------------------------------------------------------------------------------- /crazy_functions/读文章写摘要.py: -------------------------------------------------------------------------------- 1 | from toolbox import update_ui 2 | from toolbox import CatchException, report_exception 3 | from toolbox import write_history_to_file, promote_file_to_downloadzone 4 | from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive 5 | 6 | 7 | def 解析Paper(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt): 8 | import time, glob, os 9 | for index, fp in enumerate(file_manifest): 10 | with open(fp, 'r', encoding='utf-8', errors='replace') as f: 11 | file_content = f.read() 12 | 13 | prefix = "接下来请你逐文件分析下面的论文文件，概括其内容" if index==0 else "" 14 | i_say = prefix + f'请对下面的文章片段用中文做一个概述，文件名是{os.path.relpath(fp, project_folder)}，文章内容是 ```{file_content}```' 15 | i_say_show_user = prefix + f'[{index+1}/{len(file_manifest)}] 请对下面的文章片段做一个概述: {os.path.abspath(fp)}' 16 | chatbot.append((i_say_show_user, "[Local Message] waiting gpt response.")) 17 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 18 | 19 | msg = '正常' 20 | gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(i_say, i_say_show_user, llm_kwargs, chatbot, history=[], sys_prompt=system_prompt) # 带超时倒计时 21 | chatbot[-1] = (i_say_show_user, gpt_say) 22 | history.append(i_say_show_user); history.append(gpt_say) 23 | yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面 24 | time.sleep(2) 25 | 26 | all_file = ', '.join([os.path.relpath(fp, project_folder) for index, fp in enumerate(file_manifest)]) 27 | i_say = f'根据以上你自己的分析，对全文进行概括，用学术性语言写一段中文摘要，然后再写一段英文摘要（包括{all_file}）。' 28 | chatbot.append((i_say, "[Local Message] waiting gpt response.")) 29 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 30 | 31 | msg = '正常' 32 | # ** gpt request ** 33 | gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(i_say, i_say, llm_kwargs, chatbot, history=history, sys_prompt=system_prompt) # 带超时倒计时 34 | 35 | chatbot[-1] = (i_say, gpt_say) 36 | history.append(i_say); history.append(gpt_say) 37 | yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面 38 | res = write_history_to_file(history) 39 | promote_file_to_downloadzone(res, chatbot=chatbot) 40 | chatbot.append(("完成了吗？", res)) 41 | yield from update_ui(chatbot=chatbot, history=history, msg=msg) # 刷新界面 42 | 43 | 44 | 45 | @CatchException 46 | def 读文章写摘要(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request): 47 | history = [] # 清空历史，以免输入溢出 48 | import glob, os 49 | if os.path.exists(txt): 50 | project_folder = txt 51 | else: 52 | if txt == "": txt = '空空如也的输入栏' 53 | report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}") 54 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 55 | return 56 | file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.tex', recursive=True)] # + \ 57 | # [f for f in glob.glob(f'{project_folder}/**/*.cpp', recursive=True)] + \ 58 | # [f for f in glob.glob(f'{project_folder}/**/*.c', recursive=True)] 59 | if len(file_manifest) == 0: 60 | report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex文件: {txt}") 61 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 62 | return 63 | yield from 解析Paper(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt) 64 | -------------------------------------------------------------------------------- /crazy_functions/辅助功能.py: -------------------------------------------------------------------------------- 1 | # encoding: utf-8 2 | # @Time : 2023/4/19 3 | # @Author : Spike 4 | # @Descr : 5 | from toolbox import update_ui, get_conf, get_user 6 | from toolbox import CatchException 7 | from toolbox import default_user_name 8 | from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive 9 | import shutil 10 | import os 11 | 12 | 13 | @CatchException 14 | def 猜你想问(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request): 15 | if txt: 16 | show_say = txt 17 | prompt = txt+'\n回答完问题后，再列出用户可能提出的三个问题。' 18 | else: 19 | prompt = history[-1]+"\n分析上述回答，再列出用户可能提出的三个问题。" 20 | show_say = '分析上述回答，再列出用户可能提出的三个问题。' 21 | gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive( 22 | inputs=prompt, 23 | inputs_show_user=show_say, 24 | llm_kwargs=llm_kwargs, 25 | chatbot=chatbot, 26 | history=history, 27 | sys_prompt=system_prompt 28 | ) 29 | chatbot[-1] = (show_say, gpt_say) 30 | history.extend([show_say, gpt_say]) 31 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 32 | 33 | 34 | @CatchException 35 | def 清除缓存(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request): 36 | chatbot.append(['清除本地缓存数据', '执行中. 删除数据']) 37 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 38 | 39 | def _get_log_folder(user=default_user_name): 40 | PATH_LOGGING = get_conf('PATH_LOGGING') 41 | _dir = os.path.join(PATH_LOGGING, user) 42 | if not os.path.exists(_dir): os.makedirs(_dir) 43 | return _dir 44 | 45 | def _get_upload_folder(user=default_user_name): 46 | PATH_PRIVATE_UPLOAD = get_conf('PATH_PRIVATE_UPLOAD') 47 | _dir = os.path.join(PATH_PRIVATE_UPLOAD, user) 48 | return _dir 49 | 50 | shutil.rmtree(_get_log_folder(get_user(chatbot)), ignore_errors=True) 51 | shutil.rmtree(_get_upload_folder(get_user(chatbot)), ignore_errors=True) 52 | 53 | chatbot.append(['清除本地缓存数据', '执行完成']) 54 | yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 -------------------------------------------------------------------------------- /docs/Dockerfile+ChatGLM: -------------------------------------------------------------------------------- 1 | # 此Dockerfile不再维护，请前往docs/GithubAction+ChatGLM+Moss 2 | -------------------------------------------------------------------------------- /docs/Dockerfile+NoLocal+Latex: -------------------------------------------------------------------------------- 1 | # 此Dockerfile不再维护，请前往docs/GithubAction+NoLocal+Latex 2 | -------------------------------------------------------------------------------- /docs/GithubAction+AllCapacity: -------------------------------------------------------------------------------- 1 | # docker build -t gpt-academic-all-capacity -f docs/GithubAction+AllCapacity --network=host --build-arg http_proxy=http://localhost:10881 --build-arg https_proxy=http://localhost:10881 . 2 | 3 | # 从NVIDIA源，从而支持显卡（检查宿主的nvidia-smi中的cuda版本必须>=11.3） 4 | FROM fuqingxu/11.3.1-runtime-ubuntu20.04-with-texlive:latest 5 | 6 | # edge-tts需要的依赖，某些pip包所需的依赖 7 | RUN apt update && apt install ffmpeg build-essential -y 8 | RUN apt-get install -y fontconfig 9 | RUN ln -s /usr/local/texlive/2023/texmf-dist/fonts/truetype /usr/share/fonts/truetype/texlive 10 | RUN fc-cache -fv 11 | RUN apt-get clean 12 | 13 | # use python3 as the system default python 14 | WORKDIR /gpt 15 | RUN curl -sS https://bootstrap.pypa.io/get-pip.py | python3.8 16 | # 下载pytorch 17 | RUN python3 -m pip install torch --extra-index-url https://download.pytorch.org/whl/cu113 18 | # 准备pip依赖 19 | RUN python3 -m pip install openai numpy arxiv rich 20 | RUN python3 -m pip install colorama Markdown pygments pymupdf 21 | RUN python3 -m pip install python-docx moviepy pdfminer 22 | RUN python3 -m pip install zh_langchain==0.2.1 pypinyin 23 | RUN python3 -m pip install rarfile py7zr 24 | RUN python3 -m pip install aliyun-python-sdk-core==2.13.3 pyOpenSSL webrtcvad scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git 25 | # 下载分支 26 | WORKDIR /gpt 27 | RUN git clone --depth=1 https://github.com/binary-husky/gpt_academic.git 28 | WORKDIR /gpt/gpt_academic 29 | RUN git clone --depth=1 https://github.com/OpenLMLab/MOSS.git request_llms/moss 30 | 31 | RUN python3 -m pip install -r requirements.txt 32 | RUN python3 -m pip install -r request_llms/requirements_moss.txt 33 | RUN python3 -m pip install -r request_llms/requirements_qwen.txt 34 | RUN python3 -m pip install -r request_llms/requirements_chatglm.txt 35 | RUN python3 -m pip install -r request_llms/requirements_newbing.txt 36 | RUN python3 -m pip install nougat-ocr 37 | RUN python3 -m pip cache purge 38 | 39 | # 预热Tiktoken模块 40 | RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()' 41 | 42 | # 启动 43 | CMD ["python3", "-u", "main.py"] 44 | -------------------------------------------------------------------------------- /docs/GithubAction+ChatGLM+Moss: -------------------------------------------------------------------------------- 1 | 2 | # 从NVIDIA源，从而支持显卡运损（检查宿主的nvidia-smi中的cuda版本必须>=11.3） 3 | FROM nvidia/cuda:11.3.1-runtime-ubuntu20.04 4 | RUN apt-get update 5 | RUN apt-get install -y curl proxychains curl gcc 6 | RUN apt-get install -y git python python3 python-dev python3-dev --fix-missing 7 | 8 | # edge-tts需要的依赖，某些pip包所需的依赖 9 | RUN apt update && apt install ffmpeg build-essential -y 10 | RUN apt-get clean 11 | 12 | # use python3 as the system default python 13 | RUN curl -sS https://bootstrap.pypa.io/get-pip.py | python3.8 14 | # 下载pytorch 15 | RUN python3 -m pip install torch --extra-index-url https://download.pytorch.org/whl/cu113 16 | # 下载分支 17 | WORKDIR /gpt 18 | RUN git clone --depth=1 https://github.com/binary-husky/gpt_academic.git 19 | WORKDIR /gpt/gpt_academic 20 | RUN git clone https://github.com/OpenLMLab/MOSS.git request_llms/moss 21 | RUN python3 -m pip install -r requirements.txt 22 | RUN python3 -m pip install -r request_llms/requirements_moss.txt 23 | RUN python3 -m pip install -r request_llms/requirements_qwen.txt 24 | RUN python3 -m pip install -r request_llms/requirements_chatglm.txt 25 | RUN python3 -m pip install -r request_llms/requirements_newbing.txt 26 | RUN python3 -m pip cache purge 27 | 28 | 29 | # 预热Tiktoken模块 30 | RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()' 31 | 32 | # 启动 33 | CMD ["python3", "-u", "main.py"] 34 | -------------------------------------------------------------------------------- /docs/GithubAction+JittorLLMs: -------------------------------------------------------------------------------- 1 | # 从NVIDIA源，从而支持显卡运损（检查宿主的nvidia-smi中的cuda版本必须>=11.3） 2 | FROM nvidia/cuda:11.3.1-runtime-ubuntu20.04 3 | ARG useProxyNetwork='' 4 | RUN apt-get update 5 | RUN apt-get install -y curl proxychains curl g++ 6 | RUN apt-get install -y git python python3 python-dev python3-dev --fix-missing 7 | 8 | # use python3 as the system default python 9 | RUN curl -sS https://bootstrap.pypa.io/get-pip.py | python3.8 10 | 11 | # 下载pytorch 12 | RUN python3 -m pip install torch --extra-index-url https://download.pytorch.org/whl/cu113 13 | 14 | # 下载分支 15 | WORKDIR /gpt 16 | RUN git clone --depth=1 https://github.com/binary-husky/gpt_academic.git 17 | WORKDIR /gpt/gpt_academic 18 | RUN python3 -m pip install -r requirements.txt 19 | RUN python3 -m pip install -r request_llms/requirements_chatglm.txt 20 | RUN python3 -m pip install -r request_llms/requirements_newbing.txt 21 | RUN python3 -m pip install -r request_llms/requirements_jittorllms.txt -i https://pypi.jittor.org/simple -I 22 | 23 | # 下载JittorLLMs 24 | RUN git clone https://github.com/binary-husky/JittorLLMs.git --depth 1 request_llms/jittorllms 25 | 26 | # edge-tts需要的依赖 27 | RUN apt update && apt install ffmpeg -y 28 | 29 | # 禁用缓存，确保更新代码 30 | ADD "https://www.random.org/cgi-bin/randbyte?nbytes=10&format=h" skipcache 31 | RUN git pull 32 | 33 | # 预热Tiktoken模块 34 | RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()' 35 | 36 | # 启动 37 | CMD ["python3", "-u", "main.py"] 38 | -------------------------------------------------------------------------------- /docs/GithubAction+NoLocal: -------------------------------------------------------------------------------- 1 | # 此Dockerfile适用于“无本地模型”的环境构建，如果需要使用chatglm等本地模型，请参考 docs/Dockerfile+ChatGLM 2 | # 如何构建: 先修改 `config.py`， 然后 docker build -t gpt-academic-nolocal -f docs/Dockerfile+NoLocal . 3 | # 如何运行: docker run --rm -it --net=host gpt-academic-nolocal 4 | FROM python:3.11 5 | 6 | # 指定路径 7 | WORKDIR /gpt 8 | 9 | # 装载项目文件 10 | COPY . . 11 | 12 | # 安装依赖 13 | RUN pip3 install -r requirements.txt 14 | 15 | # edge-tts需要的依赖 16 | RUN apt update && apt install ffmpeg -y 17 | 18 | # 可选步骤，用于预热模块 19 | RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()' 20 | 21 | RUN python3 -m pip cache purge && apt-get clean 22 | 23 | # 启动 24 | CMD ["python3", "-u", "main.py"] 25 | -------------------------------------------------------------------------------- /docs/GithubAction+NoLocal+AudioAssistant: -------------------------------------------------------------------------------- 1 | # 此Dockerfile适用于“无本地模型”的环境构建，如果需要使用chatglm等本地模型，请参考 docs/Dockerfile+ChatGLM 2 | # 如何构建: 先修改 `config.py`， 然后 docker build -t gpt-academic-nolocal -f docs/Dockerfile+NoLocal . 3 | # 如何运行: docker run --rm -it --net=host gpt-academic-nolocal 4 | FROM python:3.11 5 | 6 | # 指定路径 7 | WORKDIR /gpt 8 | 9 | # 装载项目文件 10 | COPY . . 11 | 12 | # 安装依赖 13 | RUN pip3 install -r requirements.txt 14 | 15 | # 安装语音插件的额外依赖 16 | RUN pip3 install aliyun-python-sdk-core==2.13.3 pyOpenSSL webrtcvad scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git 17 | 18 | # edge-tts需要的依赖 19 | RUN apt update && apt install ffmpeg -y 20 | 21 | # 可选步骤，用于预热模块 22 | RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()' 23 | 24 | # 启动 25 | CMD ["python3", "-u", "main.py"] 26 | -------------------------------------------------------------------------------- /docs/GithubAction+NoLocal+Latex: -------------------------------------------------------------------------------- 1 | # 此Dockerfile适用于"无本地模型"的环境构建，如果需要使用chatglm等本地模型，请参考 docs/Dockerfile+ChatGLM 2 | # - 1 修改 `config.py` 3 | # - 2 构建 docker build -t gpt-academic-nolocal-latex -f docs/GithubAction+NoLocal+Latex . 4 | # - 3 运行 docker run -v /home/fuqingxu/arxiv_cache:/root/arxiv_cache --rm -it --net=host gpt-academic-nolocal-latex 5 | 6 | FROM menghuan1918/ubuntu_uv_ctex:latest 7 | ENV DEBIAN_FRONTEND=noninteractive 8 | SHELL ["/bin/bash", "-c"] 9 | WORKDIR /gpt 10 | 11 | # 先复制依赖文件 12 | COPY requirements.txt . 13 | 14 | # 安装依赖 15 | RUN pip install --break-system-packages openai numpy arxiv rich colorama Markdown pygments pymupdf python-docx pdfminer \ 16 | && pip install --break-system-packages -r requirements.txt \ 17 | && if [ "$(uname -m)" = "x86_64" ]; then \ 18 | pip install --break-system-packages nougat-ocr; \ 19 | fi \ 20 | && pip cache purge \ 21 | && rm -rf /root/.cache/pip/* 22 | 23 | # 创建非root用户 24 | RUN useradd -m gptuser && chown -R gptuser /gpt 25 | USER gptuser 26 | 27 | # 最后才复制代码文件,这样代码更新时只需重建最后几层，可以大幅减少docker pull所需的大小 28 | COPY --chown=gptuser:gptuser . . 29 | 30 | # 可选步骤，用于预热模块 31 | RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()' 32 | 33 | RUN python3 -m pip cache purge 34 | 35 | # 启动 36 | CMD ["python3", "-u", "main.py"] 37 | -------------------------------------------------------------------------------- /docs/GithubAction+NoLocal+Vectordb: -------------------------------------------------------------------------------- 1 | # 此Dockerfile适用于“无本地模型”的环境构建，如果需要使用chatglm等本地模型，请参考 docs/Dockerfile+ChatGLM 2 | # 如何构建: 先修改 `config.py`， 然后 docker build -t gpt-academic-nolocal-vs -f docs/GithubAction+NoLocal+Vectordb . 3 | # 如何运行: docker run --rm -it --net=host gpt-academic-nolocal-vs 4 | FROM python:3.11 5 | 6 | # 指定路径 7 | WORKDIR /gpt 8 | 9 | # 装载项目文件 10 | COPY . . 11 | 12 | # 安装依赖 13 | RUN pip3 install -r requirements.txt 14 | 15 | # 安装知识库插件的额外依赖 16 | RUN apt-get update && apt-get install libgl1 -y 17 | RUN pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cpu 18 | RUN pip3 install transformers protobuf langchain sentence-transformers faiss-cpu nltk beautifulsoup4 bitsandbytes tabulate icetk --upgrade 19 | RUN pip3 install unstructured[all-docs] --upgrade 20 | RUN python3 -c 'from check_proxy import warm_up_vectordb; warm_up_vectordb()' 21 | 22 | # edge-tts需要的依赖 23 | RUN apt update && apt install ffmpeg -y 24 | 25 | # 可选步骤，用于预热模块 26 | RUN python3 -c 'from check_proxy import warm_up_modules; warm_up_modules()' 27 | RUN python3 -m pip cache purge && apt-get clean 28 | 29 | 30 | # 启动 31 | CMD ["python3", "-u", "main.py"] 32 | -------------------------------------------------------------------------------- /docs/WindowsRun.bat: -------------------------------------------------------------------------------- 1 | @echo off 2 | setlocal 3 | 4 | :: 设置环境变量 5 | set ENV_NAME=gpt 6 | set ENV_PATH=%~dp0%ENV_NAME% 7 | set SCRIPT_PATH=%~dp0main.py 8 | 9 | :: 判断环境是否已解压 10 | if not exist "%ENV_PATH%" ( 11 | echo Extracting environment... 12 | mkdir "%ENV_PATH%" 13 | tar -xzf gpt.tar.gz -C "%ENV_PATH%" 14 | 15 | :: 运行conda环境激活脚本 16 | call "%ENV_PATH%\Scripts\activate.bat" 17 | ) else ( 18 | :: 如果环境已存在,直接激活 19 | call "%ENV_PATH%\Scripts\activate.bat" 20 | ) 21 | echo Start to run program: 22 | :: 运行Python脚本 23 | python "%SCRIPT_PATH%" 24 | 25 | endlocal 26 | pause -------------------------------------------------------------------------------- /docs/WithFastapi.md: -------------------------------------------------------------------------------- 1 | # Running with fastapi 2 | 3 | We currently support fastapi in order to solve sub-path deploy issue. 4 | 5 | 1. change CUSTOM_PATH setting in `config.py` 6 | 7 | ```sh 8 | nano config.py 9 | ``` 10 | 11 | 2. Edit main.py 12 | 13 | ```diff 14 | auto_opentab_delay() 15 | - demo.queue(concurrency_count=CONCURRENT_COUNT).launch(server_name="0.0.0.0", server_port=PORT, auth=AUTHENTICATION, favicon_path="docs/logo.png") 16 | + demo.queue(concurrency_count=CONCURRENT_COUNT) 17 | 18 | - # 如果需要在二级路径下运行 19 | - # CUSTOM_PATH = get_conf('CUSTOM_PATH') 20 | - # if CUSTOM_PATH != "/": 21 | - # from toolbox import run_gradio_in_subpath 22 | - # run_gradio_in_subpath(demo, auth=AUTHENTICATION, port=PORT, custom_path=CUSTOM_PATH) 23 | - # else: 24 | - # demo.launch(server_name="0.0.0.0", server_port=PORT, auth=AUTHENTICATION, favicon_path="docs/logo.png") 25 | 26 | + 如果需要在二级路径下运行 27 | + CUSTOM_PATH = get_conf('CUSTOM_PATH') 28 | + if CUSTOM_PATH != "/": 29 | + from toolbox import run_gradio_in_subpath 30 | + run_gradio_in_subpath(demo, auth=AUTHENTICATION, port=PORT, custom_path=CUSTOM_PATH) 31 | + else: 32 | + demo.launch(server_name="0.0.0.0", server_port=PORT, auth=AUTHENTICATION, favicon_path="docs/logo.png") 33 | 34 | if __name__ == "__main__": 35 | main() 36 | ``` 37 | 38 | 3. Go! 39 | 40 | ```sh 41 | python main.py 42 | ``` 43 | -------------------------------------------------------------------------------- /docs/demo.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/binary-husky/gpt_academic/8c2143229113ad0953b4e4dfd2a543292ce65b14/docs/demo.jpg -------------------------------------------------------------------------------- /docs/demo2.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/binary-husky/gpt_academic/8c2143229113ad0953b4e4dfd2a543292ce65b14/docs/demo2.jpg -------------------------------------------------------------------------------- /docs/logo.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/binary-husky/gpt_academic/8c2143229113ad0953b4e4dfd2a543292ce65b14/docs/logo.png -------------------------------------------------------------------------------- /docs/use_audio.md: -------------------------------------------------------------------------------- 1 | # 使用音频交互功能 2 | 3 | 4 | ## 1. 安装额外依赖 5 | ``` 6 | pip install --upgrade pyOpenSSL webrtcvad scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git 7 | ``` 8 | 9 | 如果因为特色网络问题导致上述命令无法执行： 10 | 1. git clone alibabacloud-nls-python-sdk这个项目（或者直接前往Github对应网址下载压缩包）. 11 | 命令行输入： `git clone https://github.com/aliyun/alibabacloud-nls-python-sdk.git` 12 | 1. 进入alibabacloud-nls-python-sdk目录命令行输入：`python setup.py install` 13 | 14 | 15 | ## 2. 配置音频功能开关 和 阿里云APPKEY（config.py/config_private.py/环境变量） 16 | 17 | - 注册阿里云账号 18 | - 开通 智能语音交互 （有免费白嫖时长） 19 | - 获取token和appkey 20 | - 未来将逐步用其他更廉价的云服务取代阿里云 21 | 22 | ``` 23 | ENABLE_AUDIO = True 24 | ALIYUN_TOKEN = "554a50fcd0bb476c8d07bb630e94d20c" # 此token已经失效 25 | ALIYUN_APPKEY = "RoPlZrM88DnAFkZK" # 此appkey已经失效 26 | ``` 27 | 28 | 参考 https://help.aliyun.com/document_detail/450255.html 29 | 先有阿里云开发者账号，登录之后，需要开通 智能语音交互 的功能，可以免费获得一个token，然后在 全部项目 中，创建一个项目，可以获得一个appkey. 30 | 31 | - 进阶功能 32 | 进一步填写ALIYUN_ACCESSKEY和ALIYUN_SECRET实现自动获取ALIYUN_TOKEN 33 | ``` 34 | ALIYUN_APPKEY = "RoP1ZrM84DnAFkZK" 35 | ALIYUN_TOKEN = "" 36 | ALIYUN_ACCESSKEY = "LTAI5q6BrFUzoRXVGUWnekh1" 37 | ALIYUN_SECRET = "eHmI20AVWIaQZ0CiTD2bGQVsaP9i68" 38 | ``` 39 | 40 | 41 | ## 3.启动 42 | 43 | 启动gpt-academic `python main.py` 44 | 45 | ## 4.点击record from microphe，授权音频采集 46 | 47 | I 如果需要监听自己说话（不监听电脑音频），直接在浏览器中选择对应的麦即可 48 | 49 | II 如果需要监听电脑音频（不监听自己说话），需要安装`VB-Audio VoiceMeeter`，打开声音控制面板(sound control panel) 50 | - 1 `[把电脑的所有外放声音用VoiceMeeter截留]` 在输出区（playback）选项卡，把VoiceMeeter Input虚拟设备set as default设为默认播放设备。 51 | - 2 `[把截留的声音释放到gpt-academic]` 打开gpt-academic主界面，授权音频采集后，在浏览器地址栏或者类似的地方会出现一个麦克风图标，打开后，按照浏览器的提示，选择VoiceMeeter虚拟麦克风。然后刷新页面，重新授权音频采集。 52 | - 3 `[把截留的声音同时释放到耳机或音响]` 完成第一步之后，您应处于听不到电脑声音的状态。为了在截获音频的同时，避免影响正常使用，请完成这最后一步配置。在声音控制面板(sound control panel)输入区（recording）选项卡，把VoiceMeeter Output虚拟设备set as default。双击进入VoiceMeeter Output虚拟设备的设置。 53 | - 3-1 进入VoiceMeeter Output虚拟设备子菜单，打开listen选项卡。 54 | - 3-2 勾选Listen to this device。 55 | - 3-3 在playback through this device下拉菜单中选择你的正常耳机或音响。 56 | 57 | III `[把特殊软件（如腾讯会议）的外放声音用VoiceMeeter截留]` 在完成步骤II的基础上，在特殊软件（如腾讯会议）中，打开声音菜单，选择扬声器VoiceMeeter Input，选择麦克风为正常耳机麦。 58 | 59 | VI 两种音频监听模式切换时，需要刷新页面才有效。 60 | 61 | VII 非localhost运行+非https情况下无法打开录音功能的坑：https://blog.csdn.net/weixin_39461487/article/details/109594434 62 | 63 | ## 5.点击函数插件区“实时音频采集” 或者其他音频交互功能 64 | -------------------------------------------------------------------------------- /docs/use_tts.md: -------------------------------------------------------------------------------- 1 | # 使用TTS文字转语音 2 | 3 | 4 | ## 1. 使用EDGE-TTS（简单） 5 | 6 | 将本项目配置项修改如下即可 7 | 8 | ``` 9 | TTS_TYPE = "EDGE_TTS" 10 | EDGE_TTS_VOICE = "zh-CN-XiaoxiaoNeural" 11 | ``` 12 | 13 | ## 2. 使用SoVITS（需要有显卡） 14 | 15 | 使用以下docker-compose.yml文件，先启动SoVITS服务API 16 | 17 | 1. 创建以下文件夹结构 18 | ```shell 19 | . 20 | ├── docker-compose.yml 21 | └── reference 22 | ├── clone_target_txt.txt 23 | └── clone_target_wave.mp3 24 | ``` 25 | 2. 其中`docker-compose.yml`为 26 | ```yaml 27 | version: '3.8' 28 | services: 29 | gpt-sovits: 30 | image: fuqingxu/sovits_gptac_trim:latest 31 | container_name: sovits_gptac_container 32 | working_dir: /workspace/gpt_sovits_demo 33 | environment: 34 | - is_half=False 35 | - is_share=False 36 | volumes: 37 | - ./reference:/reference 38 | ports: 39 | - "19880:9880" # 19880 为 sovits api 的暴露端口，记住它 40 | shm_size: 16G 41 | deploy: 42 | resources: 43 | reservations: 44 | devices: 45 | - driver: nvidia 46 | count: "all" 47 | capabilities: [gpu] 48 | command: bash -c "python3 api.py" 49 | ``` 50 | 3. 其中`clone_target_wave.mp3`为需要克隆的角色音频，`clone_target_txt.txt`为该音频对应的文字文本（ https://wiki.biligame.com/ys/%E8%A7%92%E8%89%B2%E8%AF%AD%E9%9F%B3 ） 51 | 4. 运行`docker-compose up` 52 | 5. 将本项目配置项修改如下即可 53 | (19880 为 sovits api 的暴露端口，与docker-compose.yml中的端口对应) 54 | ``` 55 | TTS_TYPE = "LOCAL_SOVITS_API" 56 | GPT_SOVITS_URL = "http://127.0.0.1:19880" 57 | ``` 58 | 6. 启动本项目 -------------------------------------------------------------------------------- /docs/use_vllm.md: -------------------------------------------------------------------------------- 1 | # 使用VLLM 2 | 3 | 4 | ## 1. 首先启动 VLLM，自行选择模型 5 | 6 | ``` 7 | python -m vllm.entrypoints.openai.api_server --model /home/hmp/llm/cache/Qwen1___5-32B-Chat --tensor-parallel-size 2 --dtype=half 8 | ``` 9 | 10 | 这里使用了存储在 `/home/hmp/llm/cache/Qwen1___5-32B-Chat` 的本地模型，可以根据自己的需求更改。 11 | 12 | ## 2. 测试 VLLM 13 | 14 | ``` 15 | curl http://localhost:8000/v1/chat/completions \ 16 | -H "Content-Type: application/json" \ 17 | -d '{ 18 | "model": "/home/hmp/llm/cache/Qwen1___5-32B-Chat", 19 | "messages": [ 20 | {"role": "system", "content": "You are a helpful assistant."}, 21 | {"role": "user", "content": "怎么实现一个去中心化的控制器?"} 22 | ] 23 | }' 24 | ``` 25 | 26 | ## 3. 配置本项目 27 | 28 | ``` 29 | API_KEY = "sk-123456789xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx123456789" 30 | LLM_MODEL = "vllm-/home/hmp/llm/cache/Qwen1___5-32B-Chat(max_token=4096)" 31 | API_URL_REDIRECT = {"https://api.openai.com/v1/chat/completions": "http://localhost:8000/v1/chat/completions"} 32 | ``` 33 | 34 | ``` 35 | "vllm-/home/hmp/llm/cache/Qwen1___5-32B-Chat(max_token=4096)" 36 | 其中 37 | "vllm-" 是前缀（必要） 38 | "/home/hmp/llm/cache/Qwen1___5-32B-Chat" 是模型名（必要） 39 | "(max_token=6666)" 是配置（非必要） 40 | ``` 41 | 42 | ## 4. 启动！ 43 | 44 | ``` 45 | python main.py 46 | ``` 47 | -------------------------------------------------------------------------------- /request_llms/README.md: -------------------------------------------------------------------------------- 1 | P.S. 如果您按照以下步骤成功接入了新的大模型，欢迎发Pull Requests（如果您在自己接入新模型的过程中遇到困难，欢迎加README底部QQ群联系群主） 2 | 3 | 4 | # 如何接入其他本地大语言模型 5 | 6 | 1. 复制`request_llms/bridge_llama2.py`，重命名为你喜欢的名字 7 | 8 | 2. 修改`load_model_and_tokenizer`方法，加载你的模型和分词器（去该模型官网找demo，复制粘贴即可） 9 | 10 | 3. 修改`llm_stream_generator`方法，定义推理模型（去该模型官网找demo，复制粘贴即可） 11 | 12 | 4. 命令行测试 13 | - 修改`tests/test_llms.py`（聪慧如您，只需要看一眼该文件就明白怎么修改了） 14 | - 运行`python tests/test_llms.py` 15 | 16 | 5. 测试通过后，在`request_llms/bridge_all.py`中做最后的修改，把你的模型完全接入到框架中（聪慧如您，只需要看一眼该文件就明白怎么修改了） 17 | 18 | 6. 修改`LLM_MODEL`配置，然后运行`python main.py`，测试最后的效果 19 | 20 | 21 | # 如何接入其他在线大语言模型 22 | 23 | 1. 复制`request_llms/bridge_zhipu.py`，重命名为你喜欢的名字 24 | 25 | 2. 修改`predict_no_ui_long_connection` 26 | 27 | 3. 修改`predict` 28 | 29 | 4. 命令行测试 30 | - 修改`tests/test_llms.py`（聪慧如您，只需要看一眼该文件就明白怎么修改了） 31 | - 运行`python tests/test_llms.py` 32 | 33 | 5. 测试通过后，在`request_llms/bridge_all.py`中做最后的修改，把你的模型完全接入到框架中（聪慧如您，只需要看一眼该文件就明白怎么修改了） 34 | 35 | 6. 修改`LLM_MODEL`配置，然后运行`python main.py`，测试最后的效果 36 | -------------------------------------------------------------------------------- /request_llms/bridge_chatglm4.py: -------------------------------------------------------------------------------- 1 | model_name = "ChatGLM4" 2 | cmd_to_install = """ 3 | `pip install -r request_llms/requirements_chatglm4.txt` 4 | `pip install modelscope` 5 | `modelscope download --model ZhipuAI/glm-4-9b-chat --local_dir ./THUDM/glm-4-9b-chat` 6 | """ 7 | 8 | 9 | from toolbox import get_conf, ProxyNetworkActivate 10 | from .local_llm_class import LocalLLMHandle, get_local_llm_predict_fns 11 | 12 | 13 | # ------------------------------------------------------------------------------------------------------------------------ 14 | # 🔌💻 Local Model 15 | # ------------------------------------------------------------------------------------------------------------------------ 16 | class GetGLM4Handle(LocalLLMHandle): 17 | 18 | def load_model_info(self): 19 | # 🏃‍♂️🏃‍♂️🏃‍♂️ 子进程执行 20 | self.model_name = model_name 21 | self.cmd_to_install = cmd_to_install 22 | 23 | def load_model_and_tokenizer(self): 24 | # 🏃‍♂️🏃‍♂️🏃‍♂️ 子进程执行 25 | import torch 26 | from transformers import AutoModel, AutoModelForCausalLM, AutoTokenizer 27 | import os 28 | 29 | LOCAL_MODEL_PATH, device = get_conf("CHATGLM_LOCAL_MODEL_PATH", "LOCAL_MODEL_DEVICE") 30 | model_path = LOCAL_MODEL_PATH 31 | chatglm_tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True) 32 | chatglm_model = AutoModelForCausalLM.from_pretrained( 33 | model_path, 34 | torch_dtype=torch.bfloat16, 35 | low_cpu_mem_usage=True, 36 | trust_remote_code=True, 37 | device=device 38 | ).eval().to(device) 39 | self._model = chatglm_model 40 | self._tokenizer = chatglm_tokenizer 41 | return self._model, self._tokenizer 42 | 43 | 44 | def llm_stream_generator(self, **kwargs): 45 | # 🏃‍♂️🏃‍♂️🏃‍♂️ 子进程执行 46 | def adaptor(kwargs): 47 | query = kwargs["query"] 48 | max_length = kwargs["max_length"] 49 | top_p = kwargs["top_p"] 50 | temperature = kwargs["temperature"] 51 | history = kwargs["history"] 52 | return query, max_length, top_p, temperature, history 53 | 54 | query, max_length, top_p, temperature, history = adaptor(kwargs) 55 | inputs = self._tokenizer.apply_chat_template([{"role": "user", "content": query}], 56 | add_generation_prompt=True, 57 | tokenize=True, 58 | return_tensors="pt", 59 | return_dict=True 60 | ).to(self._model.device) 61 | gen_kwargs = {"max_length": max_length, "do_sample": True, "top_k": top_p} 62 | 63 | outputs = self._model.generate(**inputs, **gen_kwargs) 64 | outputs = outputs[:, inputs['input_ids'].shape[1]:] 65 | response = self._tokenizer.decode(outputs[0], skip_special_tokens=True) 66 | yield response 67 | 68 | def try_to_import_special_deps(self, **kwargs): 69 | # import something that will raise error if the user does not install requirement_*.txt 70 | # 🏃‍♂️🏃‍♂️🏃‍♂️ 主进程执行 71 | import importlib 72 | 73 | # importlib.import_module('modelscope') 74 | 75 | 76 | # ------------------------------------------------------------------------------------------------------------------------ 77 | # 🔌💻 GPT-Academic Interface 78 | # ------------------------------------------------------------------------------------------------------------------------ 79 | predict_no_ui_long_connection, predict = get_local_llm_predict_fns( 80 | GetGLM4Handle, model_name, history_format="chatglm3" 81 | ) 82 | -------------------------------------------------------------------------------- /request_llms/bridge_chatglmonnx.py: -------------------------------------------------------------------------------- 1 | model_name = "ChatGLM-ONNX" 2 | cmd_to_install = "`pip install -r request_llms/requirements_chatglm_onnx.txt`" 3 | 4 | 5 | from transformers import AutoModel, AutoTokenizer 6 | import time 7 | import threading 8 | import importlib 9 | from toolbox import update_ui, get_conf 10 | from multiprocessing import Process, Pipe 11 | from .local_llm_class import LocalLLMHandle, get_local_llm_predict_fns 12 | 13 | from .chatglmoonx import ChatGLMModel, chat_template 14 | 15 | 16 | 17 | # ------------------------------------------------------------------------------------------------------------------------ 18 | # 🔌💻 Local Model 19 | # ------------------------------------------------------------------------------------------------------------------------ 20 | class GetONNXGLMHandle(LocalLLMHandle): 21 | 22 | def load_model_info(self): 23 | # 🏃‍♂️🏃‍♂️🏃‍♂️ 子进程执行 24 | self.model_name = model_name 25 | self.cmd_to_install = cmd_to_install 26 | 27 | def load_model_and_tokenizer(self): 28 | # 🏃‍♂️🏃‍♂️🏃‍♂️ 子进程执行 29 | import os, glob 30 | if not len(glob.glob("./request_llms/ChatGLM-6b-onnx-u8s8/chatglm-6b-int8-onnx-merged/*.bin")) >= 7: # 该模型有七个 bin 文件 31 | from huggingface_hub import snapshot_download 32 | snapshot_download(repo_id="K024/ChatGLM-6b-onnx-u8s8", local_dir="./request_llms/ChatGLM-6b-onnx-u8s8") 33 | def create_model(): 34 | return ChatGLMModel( 35 | tokenizer_path = "./request_llms/ChatGLM-6b-onnx-u8s8/chatglm-6b-int8-onnx-merged/sentencepiece.model", 36 | onnx_model_path = "./request_llms/ChatGLM-6b-onnx-u8s8/chatglm-6b-int8-onnx-merged/chatglm-6b-int8.onnx" 37 | ) 38 | self._model = create_model() 39 | return self._model, None 40 | 41 | def llm_stream_generator(self, **kwargs): 42 | # 🏃‍♂️🏃‍♂️🏃‍♂️ 子进程执行 43 | def adaptor(kwargs): 44 | query = kwargs['query'] 45 | max_length = kwargs['max_length'] 46 | top_p = kwargs['top_p'] 47 | temperature = kwargs['temperature'] 48 | history = kwargs['history'] 49 | return query, max_length, top_p, temperature, history 50 | 51 | query, max_length, top_p, temperature, history = adaptor(kwargs) 52 | 53 | prompt = chat_template(history, query) 54 | for answer in self._model.generate_iterate( 55 | prompt, 56 | max_generated_tokens=max_length, 57 | top_k=1, 58 | top_p=top_p, 59 | temperature=temperature, 60 | ): 61 | yield answer 62 | 63 | def try_to_import_special_deps(self, **kwargs): 64 | # import something that will raise error if the user does not install requirement_*.txt 65 | # 🏃‍♂️🏃‍♂️🏃‍♂️ 子进程执行 66 | pass 67 | 68 | 69 | # ------------------------------------------------------------------------------------------------------------------------ 70 | # 🔌💻 GPT-Academic Interface 71 | # ------------------------------------------------------------------------------------------------------------------------ 72 | predict_no_ui_long_connection, predict = get_local_llm_predict_fns(GetONNXGLMHandle, model_name) -------------------------------------------------------------------------------- /request_llms/bridge_qwen.py: -------------------------------------------------------------------------------- 1 | import time 2 | import os 3 | from toolbox import update_ui, get_conf, update_ui_latest_msg 4 | from toolbox import check_packages, report_exception, log_chat 5 | 6 | model_name = 'Qwen' 7 | 8 | def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", 9 | observe_window:list=[], console_silence:bool=False): 10 | """ 11 | ⭐多线程方法 12 | 函数的说明请见 request_llms/bridge_all.py 13 | """ 14 | watch_dog_patience = 5 15 | response = "" 16 | 17 | from .com_qwenapi import QwenRequestInstance 18 | sri = QwenRequestInstance() 19 | for response in sri.generate(inputs, llm_kwargs, history, sys_prompt): 20 | if len(observe_window) >= 1: 21 | observe_window[0] = response 22 | if len(observe_window) >= 2: 23 | if (time.time()-observe_window[1]) > watch_dog_patience: raise RuntimeError("程序终止。") 24 | return response 25 | 26 | def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream = True, additional_fn=None): 27 | """ 28 | ⭐单线程方法 29 | 函数的说明请见 request_llms/bridge_all.py 30 | """ 31 | chatbot.append((inputs, "")) 32 | yield from update_ui(chatbot=chatbot, history=history) 33 | 34 | # 尝试导入依赖，如果缺少依赖，则给出安装建议 35 | try: 36 | check_packages(["dashscope"]) 37 | except: 38 | yield from update_ui_latest_msg(f"导入软件依赖失败。使用该模型需要额外依赖，安装方法```pip install --upgrade dashscope```。", 39 | chatbot=chatbot, history=history, delay=0) 40 | return 41 | 42 | # 检查DASHSCOPE_API_KEY 43 | if get_conf("DASHSCOPE_API_KEY") == "": 44 | yield from update_ui_latest_msg(f"请配置 DASHSCOPE_API_KEY。", 45 | chatbot=chatbot, history=history, delay=0) 46 | return 47 | 48 | if additional_fn is not None: 49 | from core_functional import handle_core_functionality 50 | inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot) 51 | chatbot[-1] = (inputs, "") 52 | yield from update_ui(chatbot=chatbot, history=history) 53 | 54 | # 开始接收回复 55 | from .com_qwenapi import QwenRequestInstance 56 | sri = QwenRequestInstance() 57 | response = f"[Local Message] 等待{model_name}响应中 ..." 58 | for response in sri.generate(inputs, llm_kwargs, history, system_prompt): 59 | chatbot[-1] = (inputs, response) 60 | yield from update_ui(chatbot=chatbot, history=history) 61 | 62 | log_chat(llm_model=llm_kwargs["llm_model"], input_str=inputs, output_str=response) 63 | # 总结输出 64 | if response == f"[Local Message] 等待{model_name}响应中 ...": 65 | response = f"[Local Message] {model_name}响应异常 ..." 66 | history.extend([inputs, response]) 67 | yield from update_ui(chatbot=chatbot, history=history) -------------------------------------------------------------------------------- /request_llms/bridge_qwen_local.py: -------------------------------------------------------------------------------- 1 | model_name = "Qwen_Local" 2 | cmd_to_install = "`pip install -r request_llms/requirements_qwen_local.txt`" 3 | 4 | from toolbox import ProxyNetworkActivate, get_conf 5 | from .local_llm_class import LocalLLMHandle, get_local_llm_predict_fns 6 | 7 | 8 | 9 | # ------------------------------------------------------------------------------------------------------------------------ 10 | # 🔌💻 Local Model 11 | # ------------------------------------------------------------------------------------------------------------------------ 12 | class GetQwenLMHandle(LocalLLMHandle): 13 | 14 | def load_model_info(self): 15 | # 🏃‍♂️🏃‍♂️🏃‍♂️ 子进程执行 16 | self.model_name = model_name 17 | self.cmd_to_install = cmd_to_install 18 | 19 | def load_model_and_tokenizer(self): 20 | # 🏃‍♂️🏃‍♂️🏃‍♂️ 子进程执行 21 | # from modelscope import AutoModelForCausalLM, AutoTokenizer, GenerationConfig 22 | from transformers import AutoModelForCausalLM, AutoTokenizer 23 | from transformers.generation import GenerationConfig 24 | with ProxyNetworkActivate('Download_LLM'): 25 | model_id = get_conf('QWEN_LOCAL_MODEL_SELECTION') 26 | self._tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True, resume_download=True) 27 | # use fp16 28 | model = AutoModelForCausalLM.from_pretrained(model_id, device_map="auto", trust_remote_code=True).eval() 29 | model.generation_config = GenerationConfig.from_pretrained(model_id, trust_remote_code=True) # 可指定不同的生成长度、top_p等相关超参 30 | self._model = model 31 | 32 | return self._model, self._tokenizer 33 | 34 | def llm_stream_generator(self, **kwargs): 35 | # 🏃‍♂️🏃‍♂️🏃‍♂️ 子进程执行 36 | def adaptor(kwargs): 37 | query = kwargs['query'] 38 | max_length = kwargs['max_length'] 39 | top_p = kwargs['top_p'] 40 | temperature = kwargs['temperature'] 41 | history = kwargs['history'] 42 | return query, max_length, top_p, temperature, history 43 | 44 | query, max_length, top_p, temperature, history = adaptor(kwargs) 45 | 46 | for response in self._model.chat_stream(self._tokenizer, query, history=history): 47 | yield response 48 | 49 | def try_to_import_special_deps(self, **kwargs): 50 | # import something that will raise error if the user does not install requirement_*.txt 51 | # 🏃‍♂️🏃‍♂️🏃‍♂️ 主进程执行 52 | import importlib 53 | importlib.import_module('modelscope') 54 | 55 | 56 | # ------------------------------------------------------------------------------------------------------------------------ 57 | # 🔌💻 GPT-Academic Interface 58 | # ------------------------------------------------------------------------------------------------------------------------ 59 | predict_no_ui_long_connection, predict = get_local_llm_predict_fns(GetQwenLMHandle, model_name) -------------------------------------------------------------------------------- /request_llms/bridge_skylark2.py: -------------------------------------------------------------------------------- 1 | import time 2 | from toolbox import update_ui, get_conf, update_ui_latest_msg 3 | from toolbox import check_packages, report_exception 4 | 5 | model_name = '云雀大模型' 6 | 7 | def validate_key(): 8 | YUNQUE_SECRET_KEY = get_conf("YUNQUE_SECRET_KEY") 9 | if YUNQUE_SECRET_KEY == '': return False 10 | return True 11 | 12 | def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", 13 | observe_window:list=[], console_silence:bool=False): 14 | """ 15 | ⭐ 多线程方法 16 | 函数的说明请见 request_llms/bridge_all.py 17 | """ 18 | watch_dog_patience = 5 19 | response = "" 20 | 21 | if validate_key() is False: 22 | raise RuntimeError('请配置YUNQUE_SECRET_KEY') 23 | 24 | from .com_skylark2api import YUNQUERequestInstance 25 | sri = YUNQUERequestInstance() 26 | for response in sri.generate(inputs, llm_kwargs, history, sys_prompt): 27 | if len(observe_window) >= 1: 28 | observe_window[0] = response 29 | if len(observe_window) >= 2: 30 | if (time.time()-observe_window[1]) > watch_dog_patience: raise RuntimeError("程序终止。") 31 | return response 32 | 33 | def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream = True, additional_fn=None): 34 | """ 35 | ⭐ 单线程方法 36 | 函数的说明请见 request_llms/bridge_all.py 37 | """ 38 | chatbot.append((inputs, "")) 39 | yield from update_ui(chatbot=chatbot, history=history) 40 | 41 | # 尝试导入依赖，如果缺少依赖，则给出安装建议 42 | try: 43 | check_packages(["zhipuai"]) 44 | except: 45 | yield from update_ui_latest_msg(f"导入软件依赖失败。使用该模型需要额外依赖，安装方法```pip install --upgrade zhipuai```。", 46 | chatbot=chatbot, history=history, delay=0) 47 | return 48 | 49 | if validate_key() is False: 50 | yield from update_ui_latest_msg(lastmsg="[Local Message] 请配置HUOSHAN_API_KEY", chatbot=chatbot, history=history, delay=0) 51 | return 52 | 53 | if additional_fn is not None: 54 | from core_functional import handle_core_functionality 55 | inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot) 56 | 57 | # 开始接收回复 58 | from .com_skylark2api import YUNQUERequestInstance 59 | sri = YUNQUERequestInstance() 60 | response = f"[Local Message] 等待{model_name}响应中 ..." 61 | for response in sri.generate(inputs, llm_kwargs, history, system_prompt): 62 | chatbot[-1] = (inputs, response) 63 | yield from update_ui(chatbot=chatbot, history=history) 64 | 65 | # 总结输出 66 | if response == f"[Local Message] 等待{model_name}响应中 ...": 67 | response = f"[Local Message] {model_name}响应异常 ..." 68 | history.extend([inputs, response]) 69 | yield from update_ui(chatbot=chatbot, history=history) -------------------------------------------------------------------------------- /request_llms/bridge_spark.py: -------------------------------------------------------------------------------- 1 | 2 | import time 3 | import threading 4 | import importlib 5 | from toolbox import update_ui, get_conf, update_ui_latest_msg 6 | from multiprocessing import Process, Pipe 7 | 8 | model_name = '星火认知大模型' 9 | 10 | def validate_key(): 11 | XFYUN_APPID = get_conf('XFYUN_APPID') 12 | if XFYUN_APPID == '00000000' or XFYUN_APPID == '': 13 | return False 14 | return True 15 | 16 | def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", 17 | observe_window:list=[], console_silence:bool=False): 18 | """ 19 | ⭐多线程方法 20 | 函数的说明请见 request_llms/bridge_all.py 21 | """ 22 | watch_dog_patience = 5 23 | response = "" 24 | 25 | if validate_key() is False: 26 | raise RuntimeError('请配置讯飞星火大模型的XFYUN_APPID, XFYUN_API_KEY, XFYUN_API_SECRET') 27 | 28 | from .com_sparkapi import SparkRequestInstance 29 | sri = SparkRequestInstance() 30 | for response in sri.generate(inputs, llm_kwargs, history, sys_prompt, use_image_api=False): 31 | if len(observe_window) >= 1: 32 | observe_window[0] = response 33 | if len(observe_window) >= 2: 34 | if (time.time()-observe_window[1]) > watch_dog_patience: raise RuntimeError("程序终止。") 35 | return response 36 | 37 | def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream = True, additional_fn=None): 38 | """ 39 | ⭐单线程方法 40 | 函数的说明请见 request_llms/bridge_all.py 41 | """ 42 | chatbot.append((inputs, "")) 43 | yield from update_ui(chatbot=chatbot, history=history) 44 | 45 | if validate_key() is False: 46 | yield from update_ui_latest_msg(lastmsg="[Local Message] 请配置讯飞星火大模型的XFYUN_APPID, XFYUN_API_KEY, XFYUN_API_SECRET", chatbot=chatbot, history=history, delay=0) 47 | return 48 | 49 | if additional_fn is not None: 50 | from core_functional import handle_core_functionality 51 | inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot) 52 | 53 | # 开始接收回复 54 | from .com_sparkapi import SparkRequestInstance 55 | sri = SparkRequestInstance() 56 | response = f"[Local Message] 等待{model_name}响应中 ..." 57 | for response in sri.generate(inputs, llm_kwargs, history, system_prompt, use_image_api=True): 58 | chatbot[-1] = (inputs, response) 59 | yield from update_ui(chatbot=chatbot, history=history) 60 | 61 | # 总结输出 62 | if response == f"[Local Message] 等待{model_name}响应中 ...": 63 | response = f"[Local Message] {model_name}响应异常 ..." 64 | history.extend([inputs, response]) 65 | yield from update_ui(chatbot=chatbot, history=history) -------------------------------------------------------------------------------- /request_llms/bridge_taichu.py: -------------------------------------------------------------------------------- 1 | import time 2 | import os 3 | from toolbox import update_ui, get_conf, update_ui_latest_msg, log_chat 4 | from toolbox import check_packages, report_exception, have_any_recent_upload_image_files 5 | from toolbox import ChatBotWithCookies 6 | 7 | # model_name = 'Taichu-2.0' 8 | # taichu_default_model = 'taichu_llm' 9 | 10 | def validate_key(): 11 | TAICHU_API_KEY = get_conf("TAICHU_API_KEY") 12 | if TAICHU_API_KEY == '': return False 13 | return True 14 | 15 | def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", 16 | observe_window:list=[], console_silence:bool=False): 17 | """ 18 | ⭐多线程方法 19 | 函数的说明请见 request_llms/bridge_all.py 20 | """ 21 | watch_dog_patience = 5 22 | response = "" 23 | 24 | # if llm_kwargs["llm_model"] == "taichu": 25 | # llm_kwargs["llm_model"] = "taichu" 26 | 27 | if validate_key() is False: 28 | raise RuntimeError('请配置 TAICHU_API_KEY') 29 | 30 | # 开始接收回复 31 | from .com_taichu import TaichuChatInit 32 | zhipu_bro_init = TaichuChatInit() 33 | for chunk, response in zhipu_bro_init.generate_chat(inputs, llm_kwargs, history, sys_prompt): 34 | if len(observe_window) >= 1: 35 | observe_window[0] = response 36 | if len(observe_window) >= 2: 37 | if (time.time() - observe_window[1]) > watch_dog_patience: 38 | raise RuntimeError("程序终止。") 39 | return response 40 | 41 | 42 | def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWithCookies, 43 | history:list=[], system_prompt:str='', stream:bool=True, additional_fn:str=None): 44 | """ 45 | ⭐单线程方法 46 | 函数的说明请见 request_llms/bridge_all.py 47 | """ 48 | chatbot.append([inputs, ""]) 49 | yield from update_ui(chatbot=chatbot, history=history) 50 | 51 | if validate_key() is False: 52 | yield from update_ui_latest_msg(lastmsg="[Local Message] 请配置ZHIPUAI_API_KEY", chatbot=chatbot, history=history, delay=0) 53 | return 54 | 55 | if additional_fn is not None: 56 | from core_functional import handle_core_functionality 57 | inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot) 58 | chatbot[-1] = [inputs, ""] 59 | yield from update_ui(chatbot=chatbot, history=history) 60 | 61 | # if llm_kwargs["llm_model"] == "taichu": 62 | # llm_kwargs["llm_model"] = taichu_default_model 63 | 64 | # 开始接收回复 65 | from .com_taichu import TaichuChatInit 66 | zhipu_bro_init = TaichuChatInit() 67 | for chunk, response in zhipu_bro_init.generate_chat(inputs, llm_kwargs, history, system_prompt): 68 | chatbot[-1] = [inputs, response] 69 | yield from update_ui(chatbot=chatbot, history=history) 70 | history.extend([inputs, response]) 71 | log_chat(llm_model=llm_kwargs["llm_model"], input_str=inputs, output_str=response) 72 | yield from update_ui(chatbot=chatbot, history=history) -------------------------------------------------------------------------------- /request_llms/com_taichu.py: -------------------------------------------------------------------------------- 1 | # encoding: utf-8 2 | # @Time : 2024/1/22 3 | # @Author : Kilig947 & binary husky 4 | # @Descr : 兼容最新的智谱Ai 5 | from toolbox import get_conf 6 | from toolbox import get_conf, encode_image, get_pictures_list 7 | import requests 8 | import json 9 | class TaichuChatInit: 10 | def __init__(self): ... 11 | 12 | def __conversation_user(self, user_input: str, llm_kwargs:dict): 13 | return {"role": "user", "content": user_input} 14 | 15 | def __conversation_history(self, history:list, llm_kwargs:dict): 16 | messages = [] 17 | conversation_cnt = len(history) // 2 18 | if conversation_cnt: 19 | for index in range(0, 2 * conversation_cnt, 2): 20 | what_i_have_asked = self.__conversation_user(history[index], llm_kwargs) 21 | what_gpt_answer = { 22 | "role": "assistant", 23 | "content": history[index + 1] 24 | } 25 | messages.append(what_i_have_asked) 26 | messages.append(what_gpt_answer) 27 | return messages 28 | 29 | def generate_chat(self, inputs:str, llm_kwargs:dict, history:list, system_prompt:str): 30 | TAICHU_API_KEY = get_conf("TAICHU_API_KEY") 31 | params = { 32 | 'api_key': TAICHU_API_KEY, 33 | 'model_code': 'taichu_llm', 34 | 'question': '\n\n'.join(history) + inputs, 35 | 'prefix': system_prompt, 36 | 'temperature': llm_kwargs.get('temperature', 0.95), 37 | 'stream_format': 'json' 38 | } 39 | 40 | api = 'https://ai-maas.wair.ac.cn/maas/v1/model_api/invoke' 41 | response = requests.post(api, json=params, stream=True) 42 | results = "" 43 | if response.status_code == 200: 44 | response.encoding = 'utf-8' 45 | for line in response.iter_lines(decode_unicode=True): 46 | try: delta = json.loads(line)['data']['content'] 47 | except: delta = json.loads(line)['choices'][0]['text'] 48 | results += delta 49 | yield delta, results 50 | else: 51 | raise ValueError 52 | 53 | 54 | if __name__ == '__main__': 55 | zhipu = TaichuChatInit() 56 | zhipu.generate_chat('你好', {'llm_model': 'glm-4'}, [], '你是WPSAi') 57 | -------------------------------------------------------------------------------- /request_llms/embed_models/bridge_all_embed.py: -------------------------------------------------------------------------------- 1 | import tiktoken, copy, re 2 | from functools import lru_cache 3 | from concurrent.futures import ThreadPoolExecutor 4 | from toolbox import get_conf, trimmed_format_exc, apply_gpt_academic_string_mask, read_one_api_model_name 5 | 6 | # Endpoint 重定向 7 | API_URL_REDIRECT, AZURE_ENDPOINT, AZURE_ENGINE = get_conf("API_URL_REDIRECT", "AZURE_ENDPOINT", "AZURE_ENGINE") 8 | openai_endpoint = "https://api.openai.com/v1/chat/completions" 9 | if not AZURE_ENDPOINT.endswith('/'): AZURE_ENDPOINT += '/' 10 | azure_endpoint = AZURE_ENDPOINT + f'openai/deployments/{AZURE_ENGINE}/chat/completions?api-version=2023-05-15' 11 | 12 | 13 | if openai_endpoint in API_URL_REDIRECT: openai_endpoint = API_URL_REDIRECT[openai_endpoint] 14 | 15 | openai_embed_endpoint = openai_endpoint.replace("chat/completions", "embeddings") 16 | 17 | from .openai_embed import OpenAiEmbeddingModel 18 | 19 | embed_model_info = { 20 | # text-embedding-3-small Increased performance over 2nd generation ada embedding model | 1,536 21 | "text-embedding-3-small": { 22 | "embed_class": OpenAiEmbeddingModel, 23 | "embed_endpoint": openai_embed_endpoint, 24 | "embed_dimension": 1536, 25 | }, 26 | 27 | # text-embedding-3-large Most capable embedding model for both english and non-english tasks | 3,072 28 | "text-embedding-3-large": { 29 | "embed_class": OpenAiEmbeddingModel, 30 | "embed_endpoint": openai_embed_endpoint, 31 | "embed_dimension": 3072, 32 | }, 33 | 34 | # text-embedding-ada-002 Most capable 2nd generation embedding model, replacing 16 first generation models | 1,536 35 | "text-embedding-ada-002": { 36 | "embed_class": OpenAiEmbeddingModel, 37 | "embed_endpoint": openai_embed_endpoint, 38 | "embed_dimension": 1536, 39 | }, 40 | } 41 | -------------------------------------------------------------------------------- /request_llms/embed_models/openai_embed.py: -------------------------------------------------------------------------------- 1 | from llama_index.embeddings.openai import OpenAIEmbedding 2 | from openai import OpenAI 3 | from toolbox import get_conf 4 | from toolbox import CatchException, update_ui, get_conf, select_api_key, get_log_folder, ProxyNetworkActivate 5 | from shared_utils.key_pattern_manager import select_api_key_for_embed_models 6 | from typing import List, Any 7 | 8 | import numpy as np 9 | 10 | def mean_agg(embeddings): 11 | """Mean aggregation for embeddings.""" 12 | return np.array(embeddings).mean(axis=0).tolist() 13 | 14 | class EmbeddingModel(): 15 | 16 | def get_agg_embedding_from_queries( 17 | self, 18 | queries: List[str], 19 | agg_fn = None, 20 | ): 21 | """Get aggregated embedding from multiple queries.""" 22 | query_embeddings = [self.get_query_embedding(query) for query in queries] 23 | agg_fn = agg_fn or mean_agg 24 | return agg_fn(query_embeddings) 25 | 26 | def get_text_embedding_batch( 27 | self, 28 | texts: List[str], 29 | show_progress: bool = False, 30 | ): 31 | return self.compute_embedding(texts, batch_mode=True) 32 | 33 | 34 | class OpenAiEmbeddingModel(EmbeddingModel): 35 | 36 | def __init__(self, llm_kwargs:dict=None): 37 | self.llm_kwargs = llm_kwargs 38 | 39 | def get_query_embedding(self, query: str): 40 | return self.compute_embedding(query) 41 | 42 | def compute_embedding(self, text="这是要计算嵌入的文本", llm_kwargs:dict=None, batch_mode=False): 43 | from .bridge_all_embed import embed_model_info 44 | 45 | # load kwargs 46 | if llm_kwargs is None: 47 | llm_kwargs = self.llm_kwargs 48 | if llm_kwargs is None: 49 | raise RuntimeError("llm_kwargs is not provided!") 50 | 51 | # setup api and req url 52 | api_key = select_api_key_for_embed_models(llm_kwargs['api_key'], llm_kwargs['embed_model']) 53 | embed_model = llm_kwargs['embed_model'] 54 | base_url = embed_model_info[llm_kwargs['embed_model']]['embed_endpoint'].replace('embeddings', '') 55 | 56 | # send and compute 57 | with ProxyNetworkActivate("Connect_OpenAI_Embedding"): 58 | self.oai_client = OpenAI(api_key=api_key, base_url=base_url) 59 | if batch_mode: 60 | input = text 61 | assert isinstance(text, list) 62 | else: 63 | input = [text] 64 | assert isinstance(text, str) 65 | res = self.oai_client.embeddings.create(input=input, model=embed_model) 66 | 67 | # parse result 68 | if batch_mode: 69 | embedding = [d.embedding for d in res.data] 70 | else: 71 | embedding = res.data[0].embedding 72 | return embedding 73 | 74 | def embedding_dimension(self, llm_kwargs=None): 75 | # load kwargs 76 | if llm_kwargs is None: 77 | llm_kwargs = self.llm_kwargs 78 | if llm_kwargs is None: 79 | raise RuntimeError("llm_kwargs is not provided!") 80 | 81 | from .bridge_all_embed import embed_model_info 82 | return embed_model_info[llm_kwargs['embed_model']]['embed_dimension'] 83 | 84 | if __name__ == "__main__": 85 | pass -------------------------------------------------------------------------------- /request_llms/key_manager.py: -------------------------------------------------------------------------------- 1 | import random 2 | 3 | def Singleton(cls): 4 | _instance = {} 5 | 6 | def _singleton(*args, **kargs): 7 | if cls not in _instance: 8 | _instance[cls] = cls(*args, **kargs) 9 | return _instance[cls] 10 | 11 | return _singleton 12 | 13 | 14 | @Singleton 15 | class OpenAI_ApiKeyManager(): 16 | def __init__(self, mode='blacklist') -> None: 17 | # self.key_avail_list = [] 18 | self.key_black_list = [] 19 | 20 | def add_key_to_blacklist(self, key): 21 | self.key_black_list.append(key) 22 | 23 | def select_avail_key(self, key_list): 24 | # select key from key_list, but avoid keys also in self.key_black_list, raise error if no key can be found 25 | available_keys = [key for key in key_list if key not in self.key_black_list] 26 | if not available_keys: 27 | raise KeyError("No available key found.") 28 | selected_key = random.choice(available_keys) 29 | return selected_key -------------------------------------------------------------------------------- /request_llms/queued_pipe.py: -------------------------------------------------------------------------------- 1 | from multiprocessing import Pipe, Queue 2 | import time 3 | import threading 4 | 5 | class PipeSide(object): 6 | def __init__(self, q_2remote, q_2local) -> None: 7 | self.q_2remote = q_2remote 8 | self.q_2local = q_2local 9 | 10 | def recv(self): 11 | return self.q_2local.get() 12 | 13 | def send(self, buf): 14 | self.q_2remote.put(buf) 15 | 16 | def poll(self): 17 | return not self.q_2local.empty() 18 | 19 | def create_queue_pipe(): 20 | q_p2c = Queue() 21 | q_c2p = Queue() 22 | pipe_c = PipeSide(q_2local=q_p2c, q_2remote=q_c2p) 23 | pipe_p = PipeSide(q_2local=q_c2p, q_2remote=q_p2c) 24 | return pipe_c, pipe_p 25 | -------------------------------------------------------------------------------- /request_llms/requirements_chatglm.txt: -------------------------------------------------------------------------------- 1 | protobuf 2 | cpm_kernels 3 | torch>=1.10 4 | mdtex2html 5 | sentencepiece 6 | -------------------------------------------------------------------------------- /request_llms/requirements_chatglm4.txt: -------------------------------------------------------------------------------- 1 | protobuf 2 | cpm_kernels 3 | torch>=1.10 4 | transformers>=4.44 5 | mdtex2html 6 | sentencepiece 7 | accelerate -------------------------------------------------------------------------------- /request_llms/requirements_chatglm_onnx.txt: -------------------------------------------------------------------------------- 1 | protobuf 2 | cpm_kernels 3 | torch>=1.10 4 | mdtex2html 5 | sentencepiece 6 | numpy 7 | onnxruntime 8 | sentencepiece 9 | -------------------------------------------------------------------------------- /request_llms/requirements_jittorllms.txt: -------------------------------------------------------------------------------- 1 | jittor >= 1.3.7.9 2 | jtorch >= 0.1.3 3 | torch 4 | torchvision 5 | pandas 6 | jieba 7 | -------------------------------------------------------------------------------- /request_llms/requirements_moss.txt: -------------------------------------------------------------------------------- 1 | torch 2 | sentencepiece 3 | datasets 4 | accelerate 5 | matplotlib 6 | huggingface_hub 7 | triton 8 | -------------------------------------------------------------------------------- /request_llms/requirements_newbing.txt: -------------------------------------------------------------------------------- 1 | BingImageCreator 2 | certifi 3 | httpx 4 | prompt_toolkit 5 | requests 6 | rich 7 | websockets 8 | httpx[socks] 9 | -------------------------------------------------------------------------------- /request_llms/requirements_qwen.txt: -------------------------------------------------------------------------------- 1 | dashscope 2 | -------------------------------------------------------------------------------- /request_llms/requirements_qwen_local.txt: -------------------------------------------------------------------------------- 1 | modelscope 2 | transformers_stream_generator 3 | auto-gptq 4 | optimum 5 | urllib3<2 6 | -------------------------------------------------------------------------------- /request_llms/requirements_slackclaude.txt: -------------------------------------------------------------------------------- 1 | slack-sdk==3.21.3 2 | -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | https://public.agent-matrix.com/publish/gradio-3.32.14-py3-none-any.whl 2 | fastapi==0.110 3 | gradio-client==0.8 4 | pypdf2==2.12.1 5 | httpx<=0.25.2 6 | zhipuai==2.0.1 7 | tiktoken>=0.3.3 8 | requests[socks] 9 | pydantic==2.9.2 10 | protobuf==3.20 11 | transformers>=4.27.1,<4.42 12 | scipdf_parser>=0.52 13 | spacy==3.7.4 14 | anthropic>=0.18.1 15 | python-markdown-math 16 | pymdown-extensions>=10.14 17 | websocket-client 18 | beautifulsoup4 19 | prompt_toolkit 20 | latex2mathml 21 | python-docx 22 | mdtex2html 23 | dashscope 24 | pyautogen 25 | colorama 26 | Markdown 27 | pygments 28 | edge-tts>=7.0.0 29 | pymupdf 30 | openai 31 | rjsmin 32 | loguru 33 | arxiv 34 | numpy 35 | rich 36 | 37 | 38 | llama-index-core==0.10.68 39 | llama-index-legacy==0.9.48 40 | llama-index-readers-file==0.1.33 41 | llama-index-readers-llama-parse==0.1.6 42 | llama-index-embeddings-azure-openai==0.1.10 43 | llama-index-embeddings-openai==0.1.10 44 | llama-parse==0.4.9 45 | mdit-py-plugins>=0.3.3 46 | linkify-it-py==2.0.3 -------------------------------------------------------------------------------- /shared_utils/char_visual_effect.py: -------------------------------------------------------------------------------- 1 | def is_full_width_char(ch): 2 | """判断给定的单个字符是否是全角字符""" 3 | if '\u4e00' <= ch <= '\u9fff': 4 | return True # 中文字符 5 | if '\uff01' <= ch <= '\uff5e': 6 | return True # 全角符号 7 | if '\u3000' <= ch <= '\u303f': 8 | return True # CJK标点符号 9 | return False 10 | 11 | def scrolling_visual_effect(text, scroller_max_len): 12 | text = text.\ 13 | replace('\n', '').replace('`', '.').replace(' ', '.').replace('
', '.....').replace('$', '.') 14 | place_take_cnt = 0 15 | pointer = len(text) - 1 16 | 17 | if len(text) < scroller_max_len: 18 | return text 19 | 20 | while place_take_cnt < scroller_max_len and pointer > 0: 21 | if is_full_width_char(text[pointer]): place_take_cnt += 2 22 | else: place_take_cnt += 1 23 | pointer -= 1 24 | 25 | return text[pointer:] -------------------------------------------------------------------------------- /shared_utils/colorful.py: -------------------------------------------------------------------------------- 1 | import platform 2 | from sys import stdout 3 | from loguru import logger 4 | 5 | if platform.system()=="Linux": 6 | pass 7 | else: 8 | from colorama import init 9 | init() 10 | 11 | # Do you like the elegance of Chinese characters? 12 | def print红(*kw,**kargs): 13 | print("\033[0;31m",*kw,"\033[0m",**kargs) 14 | def print绿(*kw,**kargs): 15 | print("\033[0;32m",*kw,"\033[0m",**kargs) 16 | def print黄(*kw,**kargs): 17 | print("\033[0;33m",*kw,"\033[0m",**kargs) 18 | def print蓝(*kw,**kargs): 19 | print("\033[0;34m",*kw,"\033[0m",**kargs) 20 | def print紫(*kw,**kargs): 21 | print("\033[0;35m",*kw,"\033[0m",**kargs) 22 | def print靛(*kw,**kargs): 23 | print("\033[0;36m",*kw,"\033[0m",**kargs) 24 | 25 | def print亮红(*kw,**kargs): 26 | print("\033[1;31m",*kw,"\033[0m",**kargs) 27 | def print亮绿(*kw,**kargs): 28 | print("\033[1;32m",*kw,"\033[0m",**kargs) 29 | def print亮黄(*kw,**kargs): 30 | print("\033[1;33m",*kw,"\033[0m",**kargs) 31 | def print亮蓝(*kw,**kargs): 32 | print("\033[1;34m",*kw,"\033[0m",**kargs) 33 | def print亮紫(*kw,**kargs): 34 | print("\033[1;35m",*kw,"\033[0m",**kargs) 35 | def print亮靛(*kw,**kargs): 36 | print("\033[1;36m",*kw,"\033[0m",**kargs) 37 | 38 | # Do you like the elegance of Chinese characters? 39 | def sprint红(*kw): 40 | return "\033[0;31m"+' '.join(kw)+"\033[0m" 41 | def sprint绿(*kw): 42 | return "\033[0;32m"+' '.join(kw)+"\033[0m" 43 | def sprint黄(*kw): 44 | return "\033[0;33m"+' '.join(kw)+"\033[0m" 45 | def sprint蓝(*kw): 46 | return "\033[0;34m"+' '.join(kw)+"\033[0m" 47 | def sprint紫(*kw): 48 | return "\033[0;35m"+' '.join(kw)+"\033[0m" 49 | def sprint靛(*kw): 50 | return "\033[0;36m"+' '.join(kw)+"\033[0m" 51 | def sprint亮红(*kw): 52 | return "\033[1;31m"+' '.join(kw)+"\033[0m" 53 | def sprint亮绿(*kw): 54 | return "\033[1;32m"+' '.join(kw)+"\033[0m" 55 | def sprint亮黄(*kw): 56 | return "\033[1;33m"+' '.join(kw)+"\033[0m" 57 | def sprint亮蓝(*kw): 58 | return "\033[1;34m"+' '.join(kw)+"\033[0m" 59 | def sprint亮紫(*kw): 60 | return "\033[1;35m"+' '.join(kw)+"\033[0m" 61 | def sprint亮靛(*kw): 62 | return "\033[1;36m"+' '.join(kw)+"\033[0m" 63 | 64 | def log红(*kw,**kargs): 65 | logger.opt(depth=1).info(sprint红(*kw)) 66 | def log绿(*kw,**kargs): 67 | logger.opt(depth=1).info(sprint绿(*kw)) 68 | def log黄(*kw,**kargs): 69 | logger.opt(depth=1).info(sprint黄(*kw)) 70 | def log蓝(*kw,**kargs): 71 | logger.opt(depth=1).info(sprint蓝(*kw)) 72 | def log紫(*kw,**kargs): 73 | logger.opt(depth=1).info(sprint紫(*kw)) 74 | def log靛(*kw,**kargs): 75 | logger.opt(depth=1).info(sprint靛(*kw)) 76 | 77 | def log亮红(*kw,**kargs): 78 | logger.opt(depth=1).info(sprint亮红(*kw)) 79 | def log亮绿(*kw,**kargs): 80 | logger.opt(depth=1).info(sprint亮绿(*kw)) 81 | def log亮黄(*kw,**kargs): 82 | logger.opt(depth=1).info(sprint亮黄(*kw)) 83 | def log亮蓝(*kw,**kargs): 84 | logger.opt(depth=1).info(sprint亮蓝(*kw)) 85 | def log亮紫(*kw,**kargs): 86 | logger.opt(depth=1).info(sprint亮紫(*kw)) 87 | def log亮靛(*kw,**kargs): 88 | logger.opt(depth=1).info(sprint亮靛(*kw)) -------------------------------------------------------------------------------- /shared_utils/connect_void_terminal.py: -------------------------------------------------------------------------------- 1 | import os 2 | 3 | """ 4 | =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- 5 | 接驳void-terminal: 6 | - set_conf: 在运行过程中动态地修改配置 7 | - set_multi_conf: 在运行过程中动态地修改多个配置 8 | - get_plugin_handle: 获取插件的句柄 9 | - get_plugin_default_kwargs: 获取插件的默认参数 10 | - get_chat_handle: 获取简单聊天的句柄 11 | - get_chat_default_kwargs: 获取简单聊天的默认参数 12 | =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=- 13 | """ 14 | 15 | 16 | def get_plugin_handle(plugin_name): 17 | """ 18 | e.g. plugin_name = 'crazy_functions.Markdown_Translate->Markdown翻译指定语言' 19 | """ 20 | import importlib 21 | 22 | assert ( 23 | "->" in plugin_name 24 | ), "Example of plugin_name: crazy_functions.Markdown_Translate->Markdown翻译指定语言" 25 | module, fn_name = plugin_name.split("->") 26 | f_hot_reload = getattr(importlib.import_module(module, fn_name), fn_name) 27 | return f_hot_reload 28 | 29 | 30 | def get_chat_handle(): 31 | """ 32 | Get chat function 33 | """ 34 | from request_llms.bridge_all import predict_no_ui_long_connection 35 | 36 | return predict_no_ui_long_connection 37 | 38 | 39 | def get_plugin_default_kwargs(): 40 | """ 41 | Get Plugin Default Arguments 42 | """ 43 | from toolbox import ChatBotWithCookies, load_chat_cookies 44 | 45 | cookies = load_chat_cookies() 46 | llm_kwargs = { 47 | "api_key": cookies["api_key"], 48 | "llm_model": cookies["llm_model"], 49 | "top_p": 1.0, 50 | "max_length": None, 51 | "temperature": 1.0, 52 | } 53 | chatbot = ChatBotWithCookies(llm_kwargs) 54 | 55 | # txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_request 56 | DEFAULT_FN_GROUPS_kwargs = { 57 | "main_input": "./README.md", 58 | "llm_kwargs": llm_kwargs, 59 | "plugin_kwargs": {}, 60 | "chatbot_with_cookie": chatbot, 61 | "history": [], 62 | "system_prompt": "You are a good AI.", 63 | "user_request": None, 64 | } 65 | return DEFAULT_FN_GROUPS_kwargs 66 | 67 | 68 | def get_chat_default_kwargs(): 69 | """ 70 | Get Chat Default Arguments 71 | """ 72 | from toolbox import load_chat_cookies 73 | 74 | cookies = load_chat_cookies() 75 | llm_kwargs = { 76 | "api_key": cookies["api_key"], 77 | "llm_model": cookies["llm_model"], 78 | "top_p": 1.0, 79 | "max_length": None, 80 | "temperature": 1.0, 81 | } 82 | default_chat_kwargs = { 83 | "inputs": "Hello there, are you ready?", 84 | "llm_kwargs": llm_kwargs, 85 | "history": [], 86 | "sys_prompt": "You are AI assistant", 87 | "observe_window": None, 88 | "console_silence": False, 89 | } 90 | 91 | return default_chat_kwargs 92 | -------------------------------------------------------------------------------- /shared_utils/logging.py: -------------------------------------------------------------------------------- 1 | from loguru import logger 2 | import logging 3 | import sys 4 | import os 5 | 6 | def chat_log_filter(record): 7 | return "chat_msg" in record["extra"] 8 | 9 | def not_chat_log_filter(record): 10 | return "chat_msg" not in record["extra"] 11 | 12 | def formatter_with_clip(record): 13 | # Note this function returns the string to be formatted, not the actual message to be logged 14 | # record["extra"]["serialized"] = "555555" 15 | max_len = 12 16 | record['function_x'] = record['function'].center(max_len) 17 | if len(record['function_x']) > max_len: 18 | record['function_x'] = ".." + record['function_x'][-(max_len-2):] 19 | record['line_x'] = str(record['line']).ljust(3) 20 | return '{time:HH:mm} | {function_x}:{line_x} | {message}\n' 21 | 22 | def setup_logging(PATH_LOGGING): 23 | 24 | admin_log_path = os.path.join(PATH_LOGGING, "admin") 25 | os.makedirs(admin_log_path, exist_ok=True) 26 | sensitive_log_path = os.path.join(admin_log_path, "chat_secrets.log") 27 | regular_log_path = os.path.join(admin_log_path, "console_log.log") 28 | logger.remove() 29 | logger.configure( 30 | levels=[dict(name="WARNING", color="")], 31 | ) 32 | 33 | logger.add( 34 | sys.stderr, 35 | format=formatter_with_clip, 36 | # format='{time:HH:mm} | {function}:{line} - {message}', 37 | filter=(lambda record: not chat_log_filter(record)), 38 | colorize=True, 39 | enqueue=True 40 | ) 41 | 42 | logger.add( 43 | sensitive_log_path, 44 | format='{time:MM-DD HH:mm:ss} | {level: <8} | {name}:{function}:{line} - {message}', 45 | rotation="10 MB", 46 | filter=chat_log_filter, 47 | enqueue=True, 48 | ) 49 | 50 | logger.add( 51 | regular_log_path, 52 | format='{time:MM-DD HH:mm:ss} | {level: <8} | {name}:{function}:{line} - {message}', 53 | rotation="10 MB", 54 | filter=not_chat_log_filter, 55 | enqueue=True, 56 | ) 57 | 58 | logging.getLogger("httpx").setLevel(logging.WARNING) 59 | 60 | logger.warning(f"所有对话记录将自动保存在本地目录{sensitive_log_path}, 请注意自我隐私保护哦！") 61 | 62 | 63 | # logger.bind(chat_msg=True).info("This message is logged to the file!") 64 | # logger.debug(f"debug message") 65 | # logger.info(f"info message") 66 | # logger.success(f"success message") 67 | # logger.error(f"error message") 68 | # logger.add("special.log", filter=lambda record: "special" in record["extra"]) 69 | # logger.debug("This message is not logged to the file") 70 | -------------------------------------------------------------------------------- /shared_utils/map_names.py: -------------------------------------------------------------------------------- 1 | import re 2 | mapping_dic = { 3 | # "qianfan": "qianfan（文心一言大模型）", 4 | # "zhipuai": "zhipuai（智谱GLM4超级模型🔥）", 5 | # "gpt-4-1106-preview": "gpt-4-1106-preview（新调优版本GPT-4🔥）", 6 | # "gpt-4-vision-preview": "gpt-4-vision-preview（识图模型GPT-4V）", 7 | } 8 | 9 | rev_mapping_dic = {} 10 | for k, v in mapping_dic.items(): 11 | rev_mapping_dic[v] = k 12 | 13 | def map_model_to_friendly_names(m): 14 | if m in mapping_dic: 15 | return mapping_dic[m] 16 | return m 17 | 18 | def map_friendly_names_to_model(m): 19 | if m in rev_mapping_dic: 20 | return rev_mapping_dic[m] 21 | return m 22 | 23 | def read_one_api_model_name(model: str): 24 | """return real model name and max_token. 25 | """ 26 | max_token_pattern = r"\(max_token=(\d+)\)" 27 | match = re.search(max_token_pattern, model) 28 | if match: 29 | max_token_tmp = match.group(1) # 获取 max_token 的值 30 | max_token_tmp = int(max_token_tmp) 31 | model = re.sub(max_token_pattern, "", model) # 从原字符串中删除 "(max_token=...)" 32 | else: 33 | max_token_tmp = 4096 34 | return model, max_token_tmp -------------------------------------------------------------------------------- /tests/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/binary-husky/gpt_academic/8c2143229113ad0953b4e4dfd2a543292ce65b14/tests/__init__.py -------------------------------------------------------------------------------- /tests/init_test.py: -------------------------------------------------------------------------------- 1 | def validate_path(): 2 | import os, sys 3 | 4 | os.path.dirname(__file__) 5 | root_dir_assume = os.path.abspath(os.path.dirname(__file__) + "/..") 6 | os.chdir(root_dir_assume) 7 | sys.path.append(root_dir_assume) 8 | 9 | 10 | validate_path() # validate path so you can run from base directory 11 | -------------------------------------------------------------------------------- /tests/test_anim_gen.py: -------------------------------------------------------------------------------- 1 | """ 2 | 对项目中的各个插件进行测试。运行方法：直接运行 python tests/test_plugins.py 3 | """ 4 | 5 | import init_test 6 | import os, sys 7 | 8 | 9 | if __name__ == "__main__": 10 | from test_utils import plugin_test 11 | 12 | plugin_test(plugin='crazy_functions.数学动画生成manim->动画生成', main_input="A point moving along function culve y=sin(x), starting from x=0 and stop at x=4*\pi.") 13 | -------------------------------------------------------------------------------- /tests/test_bilibili_down.py: -------------------------------------------------------------------------------- 1 | """ 2 | 对项目中的各个插件进行测试。运行方法：直接运行 python tests/test_plugins.py 3 | """ 4 | 5 | import init_test 6 | import os, sys 7 | 8 | if __name__ == "__main__": 9 | from experimental_mods.get_bilibili_resource import download_bilibili 10 | download_bilibili("BV1LSSHYXEtv", only_audio=True, user_name="test") 11 | 12 | # if __name__ == "__main__": 13 | # from test_utils import plugin_test 14 | 15 | # plugin_test(plugin='crazy_functions.VideoResource_GPT->视频任务', main_input="帮我找到《天文馆的猫》，歌手泠鸢") 16 | -------------------------------------------------------------------------------- /tests/test_doc2x.py: -------------------------------------------------------------------------------- 1 | import init_test 2 | 3 | from crazy_functions.pdf_fns.parse_pdf_via_doc2x import 解析PDF_DOC2X_转Latex 4 | 5 | # 解析PDF_DOC2X_转Latex("gpt_log/arxiv_cache_old/2410.10819/workfolder/merge.pdf") 6 | # 解析PDF_DOC2X_转Latex("gpt_log/arxiv_cache_ooo/2410.07095/workfolder/merge.pdf") 7 | 解析PDF_DOC2X_转Latex("2410.11190v2.pdf") 8 | -------------------------------------------------------------------------------- /tests/test_key_pattern_manager.py: -------------------------------------------------------------------------------- 1 | import unittest 2 | 3 | def validate_path(): 4 | import os, sys 5 | 6 | os.path.dirname(__file__) 7 | root_dir_assume = os.path.abspath(os.path.dirname(__file__) + "/..") 8 | os.chdir(root_dir_assume) 9 | sys.path.append(root_dir_assume) 10 | 11 | 12 | validate_path() # validate path so you can run from base directory 13 | 14 | from shared_utils.key_pattern_manager import is_openai_api_key 15 | 16 | class TestKeyPatternManager(unittest.TestCase): 17 | def test_is_openai_api_key_with_valid_key(self): 18 | key = "sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" 19 | self.assertTrue(is_openai_api_key(key)) 20 | 21 | key = "sx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" 22 | self.assertFalse(is_openai_api_key(key)) 23 | 24 | key = "sess-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" 25 | self.assertTrue(is_openai_api_key(key)) 26 | 27 | key = "sess-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" 28 | self.assertFalse(is_openai_api_key(key)) 29 | 30 | key = "sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx_xxxxxxxxxxxxxxxxxx-xxxxxxxxxxxxxxxxxxxx" 31 | self.assertTrue(is_openai_api_key(key)) 32 | key = "sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx-xxxxxxxxxxxxxxx_xxxxxxxxxxxx_xxxxx-xxxxxxxxxxxxxxxxxxxx" 33 | self.assertTrue(is_openai_api_key(key)) 34 | key = "sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx-xxx-xxxxxxxxxxxxxxx_xxxxxxxxxxxx_xxxxx-xxxxxx-xxxxxxxxxxxxx" 35 | self.assertTrue(is_openai_api_key(key)) 36 | key = "sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx-xxx-xxxxxxxxxxxxxxx_xxxxxxxxxxxx_xxxxx-xxxxxxxxxxxxxxxxxx" 37 | self.assertFalse(is_openai_api_key(key)) 38 | key = "sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx-xxx-xxxxxxxxxxxxxxx_xxxxxxxxxxxx_xxxxx-xxxxxxxxxxxxxxxxxxxxx" 39 | self.assertFalse(is_openai_api_key(key)) 40 | 41 | key = "sk-proj-xx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx_xxxxxxxxxxxxxxxxxxxxx-xxxxxxxx" 42 | self.assertTrue(is_openai_api_key(key)) 43 | key = "sk-proj-xx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx_xxxxxxxxxxxx_xxxxxxxxxxxxxxxxxxxxx-xxxxxxxx" 44 | self.assertTrue(is_openai_api_key(key)) 45 | key = "sk-proj-xx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx_xxxxxxxxxxxx_xxxxxxxxxxxxxxxxxx-xxxxxxxx" 46 | self.assertFalse(is_openai_api_key(key)) 47 | key = "sk-proj-xx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx_xxxxxxxxxxxx_xxxxxxxxxxxxxxxxxx-xxxxxxxxxxxxx" 48 | self.assertFalse(is_openai_api_key(key)) 49 | key = "sk-proj-xx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx_xxxxxxxxxxxx_xxxxxxxxxxxxxxxxxx-xxx啊xxxxxxx" 50 | self.assertFalse(is_openai_api_key(key)) 51 | 52 | 53 | def test_is_openai_api_key_with_invalid_key(self): 54 | key = "invalid_key" 55 | self.assertFalse(is_openai_api_key(key)) 56 | 57 | def test_is_openai_api_key_with_custom_pattern(self): 58 | # Assuming you have set a custom pattern in your configuration 59 | key = "custom-pattern-key" 60 | self.assertFalse(is_openai_api_key(key)) 61 | 62 | if __name__ == '__main__': 63 | unittest.main() -------------------------------------------------------------------------------- /tests/test_latex_auto_correct.py: -------------------------------------------------------------------------------- 1 | """ 2 | 对项目中的各个插件进行测试。运行方法：直接运行 python tests/test_plugins.py 3 | """ 4 | 5 | 6 | import os, sys, importlib 7 | 8 | 9 | def validate_path(): 10 | dir_name = os.path.dirname(__file__) 11 | root_dir_assume = os.path.abspath(dir_name + "/..") 12 | os.chdir(root_dir_assume) 13 | sys.path.append(root_dir_assume) 14 | 15 | 16 | validate_path() # 返回项目根路径 17 | 18 | if __name__ == "__main__": 19 | plugin_test = importlib.import_module('test_utils').plugin_test 20 | 21 | 22 | # plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="2203.01927") 23 | # plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="gpt_log/arxiv_cache/2203.01927/workfolder") 24 | # plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="2410.05779") 25 | plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="gpt_log/default_user/workfolder") 26 | 27 | -------------------------------------------------------------------------------- /tests/test_llms.py: -------------------------------------------------------------------------------- 1 | # """ 2 | # 对各个llm模型进行单元测试 3 | # """ 4 | def validate_path(): 5 | import os, sys 6 | 7 | os.path.dirname(__file__) 8 | root_dir_assume = os.path.abspath(os.path.dirname(__file__) + "/..") 9 | os.chdir(root_dir_assume) 10 | sys.path.append(root_dir_assume) 11 | 12 | 13 | validate_path() # validate path so you can run from base directory 14 | 15 | if "在线模型": 16 | if __name__ == "__main__": 17 | from request_llms.bridge_taichu import predict_no_ui_long_connection 18 | # from request_llms.bridge_cohere import predict_no_ui_long_connection 19 | # from request_llms.bridge_spark import predict_no_ui_long_connection 20 | # from request_llms.bridge_zhipu import predict_no_ui_long_connection 21 | # from request_llms.bridge_chatglm3 import predict_no_ui_long_connection 22 | llm_kwargs = { 23 | "llm_model": "taichu", 24 | "max_length": 4096, 25 | "top_p": 1, 26 | "temperature": 1, 27 | } 28 | 29 | result = predict_no_ui_long_connection( 30 | inputs="请问什么是质子？", llm_kwargs=llm_kwargs, history=["你好", "我好！"], sys_prompt="系统" 31 | ) 32 | print("final result:", result) 33 | print("final result:", result) 34 | 35 | 36 | if "本地模型": 37 | if __name__ == "__main__": 38 | # from request_llms.bridge_newbingfree import predict_no_ui_long_connection 39 | # from request_llms.bridge_moss import predict_no_ui_long_connection 40 | # from request_llms.bridge_jittorllms_pangualpha import predict_no_ui_long_connection 41 | # from request_llms.bridge_jittorllms_llama import predict_no_ui_long_connection 42 | # from request_llms.bridge_claude import predict_no_ui_long_connection 43 | # from request_llms.bridge_internlm import predict_no_ui_long_connection 44 | # from request_llms.bridge_deepseekcoder import predict_no_ui_long_connection 45 | # from request_llms.bridge_qwen_7B import predict_no_ui_long_connection 46 | # from request_llms.bridge_qwen_local import predict_no_ui_long_connection 47 | llm_kwargs = { 48 | "max_length": 4096, 49 | "top_p": 1, 50 | "temperature": 1, 51 | } 52 | result = predict_no_ui_long_connection( 53 | inputs="请问什么是质子？", llm_kwargs=llm_kwargs, history=["你好", "我好！"], sys_prompt="" 54 | ) 55 | print("final result:", result) 56 | 57 | -------------------------------------------------------------------------------- /tests/test_media.py: -------------------------------------------------------------------------------- 1 | """ 2 | 对项目中的各个插件进行测试。运行方法：直接运行 python tests/test_plugins.py 3 | """ 4 | 5 | import init_test 6 | import os, sys 7 | 8 | 9 | if __name__ == "__main__": 10 | from test_utils import plugin_test 11 | 12 | plugin_test(plugin='crazy_functions.VideoResource_GPT->多媒体任务', main_input="我想找一首歌，里面有句歌词是“turn your face towards the sun”") 13 | 14 | # plugin_test(plugin='crazy_functions.Internet_GPT->连接网络回答问题', main_input="谁是应急食品？") 15 | 16 | # plugin_test(plugin='crazy_functions.函数动态生成->函数动态生成', main_input='交换图像的蓝色通道和红色通道', advanced_arg={"file_path_arg": "./build/ants.jpg"}) 17 | 18 | # plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="2307.07522") 19 | 20 | # plugin_test(plugin='crazy_functions.PDF_Translate->批量翻译PDF文档', main_input='build/pdf/t1.pdf') 21 | 22 | # plugin_test( 23 | # plugin="crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF", 24 | # main_input="G:/SEAFILE_LOCAL/50503047/我的资料库/学位/paperlatex/aaai/Fu_8368_with_appendix", 25 | # ) 26 | 27 | # plugin_test(plugin='crazy_functions.虚空终端->虚空终端', main_input='修改api-key为sk-jhoejriotherjep') 28 | 29 | # plugin_test(plugin='crazy_functions.批量翻译PDF文档_NOUGAT->批量翻译PDF文档', main_input='crazy_functions/test_project/pdf_and_word/aaai.pdf') 30 | 31 | # plugin_test(plugin='crazy_functions.虚空终端->虚空终端', main_input='调用插件，对C:/Users/fuqingxu/Desktop/旧文件/gpt/chatgpt_academic/crazy_functions/latex_fns中的python文件进行解析') 32 | 33 | # plugin_test(plugin='crazy_functions.命令行助手->命令行助手', main_input='查看当前的docker容器列表') 34 | 35 | # plugin_test(plugin='crazy_functions.SourceCode_Analyse->解析一个Python项目', main_input="crazy_functions/test_project/python/dqn") 36 | 37 | # plugin_test(plugin='crazy_functions.SourceCode_Analyse->解析一个C项目', main_input="crazy_functions/test_project/cpp/cppipc") 38 | 39 | # plugin_test(plugin='crazy_functions.Latex_Project_Polish->Latex英文润色', main_input="crazy_functions/test_project/latex/attention") 40 | 41 | # plugin_test(plugin='crazy_functions.Markdown_Translate->Markdown中译英', main_input="README.md") 42 | 43 | # plugin_test(plugin='crazy_functions.PDF_Translate->批量翻译PDF文档', main_input='crazy_functions/test_project/pdf_and_word/aaai.pdf') 44 | 45 | # plugin_test(plugin='crazy_functions.谷歌检索小助手->谷歌检索小助手', main_input="https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=auto+reinforcement+learning&btnG=") 46 | 47 | # plugin_test(plugin='crazy_functions.总结word文档->总结word文档', main_input="crazy_functions/test_project/pdf_and_word") 48 | 49 | # plugin_test(plugin='crazy_functions.下载arxiv论文翻译摘要->下载arxiv论文并翻译摘要', main_input="1812.10695") 50 | 51 | # plugin_test(plugin='crazy_functions.解析JupyterNotebook->解析ipynb文件', main_input="crazy_functions/test_samples") 52 | 53 | # plugin_test(plugin='crazy_functions.数学动画生成manim->动画生成', main_input="A ball split into 2, and then split into 4, and finally split into 8.") 54 | 55 | # for lang in ["English", "French", "Japanese", "Korean", "Russian", "Italian", "German", "Portuguese", "Arabic"]: 56 | # plugin_test(plugin='crazy_functions.Markdown_Translate->Markdown翻译指定语言', main_input="README.md", advanced_arg={"advanced_arg": lang}) 57 | 58 | # plugin_test(plugin='crazy_functions.知识库文件注入->知识库文件注入', main_input="./") 59 | 60 | # plugin_test(plugin='crazy_functions.知识库文件注入->读取知识库作答', main_input="What is the installation method？") 61 | 62 | # plugin_test(plugin='crazy_functions.知识库文件注入->读取知识库作答', main_input="远程云服务器部署？") 63 | 64 | # plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="2210.03629") 65 | 66 | -------------------------------------------------------------------------------- /tests/test_plugins.py: -------------------------------------------------------------------------------- 1 | """ 2 | 对项目中的各个插件进行测试。运行方法：直接运行 python tests/test_plugins.py 3 | """ 4 | 5 | import init_test 6 | import os, sys 7 | 8 | 9 | if __name__ == "__main__": 10 | from test_utils import plugin_test 11 | 12 | plugin_test(plugin='crazy_functions.SourceCode_Comment->注释Python项目', main_input="build/test/python_comment") 13 | 14 | # plugin_test(plugin='crazy_functions.Internet_GPT->连接网络回答问题', main_input="谁是应急食品？") 15 | 16 | # plugin_test(plugin='crazy_functions.函数动态生成->函数动态生成', main_input='交换图像的蓝色通道和红色通道', advanced_arg={"file_path_arg": "./build/ants.jpg"}) 17 | 18 | # plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="2307.07522") 19 | 20 | # plugin_test(plugin='crazy_functions.PDF_Translate->批量翻译PDF文档', main_input='build/pdf/t1.pdf') 21 | 22 | # plugin_test( 23 | # plugin="crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF", 24 | # main_input="G:/SEAFILE_LOCAL/50503047/我的资料库/学位/paperlatex/aaai/Fu_8368_with_appendix", 25 | # ) 26 | 27 | # plugin_test(plugin='crazy_functions.虚空终端->虚空终端', main_input='修改api-key为sk-jhoejriotherjep') 28 | 29 | # plugin_test(plugin='crazy_functions.批量翻译PDF文档_NOUGAT->批量翻译PDF文档', main_input='crazy_functions/test_project/pdf_and_word/aaai.pdf') 30 | 31 | # plugin_test(plugin='crazy_functions.虚空终端->虚空终端', main_input='调用插件，对C:/Users/fuqingxu/Desktop/旧文件/gpt/chatgpt_academic/crazy_functions/latex_fns中的python文件进行解析') 32 | 33 | # plugin_test(plugin='crazy_functions.命令行助手->命令行助手', main_input='查看当前的docker容器列表') 34 | 35 | # plugin_test(plugin='crazy_functions.SourceCode_Analyse->解析一个Python项目', main_input="crazy_functions/test_project/python/dqn") 36 | 37 | # plugin_test(plugin='crazy_functions.SourceCode_Analyse->解析一个C项目', main_input="crazy_functions/test_project/cpp/cppipc") 38 | 39 | # plugin_test(plugin='crazy_functions.Latex_Project_Polish->Latex英文润色', main_input="crazy_functions/test_project/latex/attention") 40 | 41 | # plugin_test(plugin='crazy_functions.Markdown_Translate->Markdown中译英', main_input="README.md") 42 | 43 | # plugin_test(plugin='crazy_functions.PDF_Translate->批量翻译PDF文档', main_input='crazy_functions/test_project/pdf_and_word/aaai.pdf') 44 | 45 | # plugin_test(plugin='crazy_functions.谷歌检索小助手->谷歌检索小助手', main_input="https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=auto+reinforcement+learning&btnG=") 46 | 47 | # plugin_test(plugin='crazy_functions.总结word文档->总结word文档', main_input="crazy_functions/test_project/pdf_and_word") 48 | 49 | # plugin_test(plugin='crazy_functions.下载arxiv论文翻译摘要->下载arxiv论文并翻译摘要', main_input="1812.10695") 50 | 51 | # plugin_test(plugin='crazy_functions.解析JupyterNotebook->解析ipynb文件', main_input="crazy_functions/test_samples") 52 | 53 | # plugin_test(plugin='crazy_functions.数学动画生成manim->动画生成', main_input="A ball split into 2, and then split into 4, and finally split into 8.") 54 | 55 | # for lang in ["English", "French", "Japanese", "Korean", "Russian", "Italian", "German", "Portuguese", "Arabic"]: 56 | # plugin_test(plugin='crazy_functions.Markdown_Translate->Markdown翻译指定语言', main_input="README.md", advanced_arg={"advanced_arg": lang}) 57 | 58 | # plugin_test(plugin='crazy_functions.知识库文件注入->知识库文件注入', main_input="./") 59 | 60 | # plugin_test(plugin='crazy_functions.知识库文件注入->读取知识库作答', main_input="What is the installation method？") 61 | 62 | # plugin_test(plugin='crazy_functions.知识库文件注入->读取知识库作答', main_input="远程云服务器部署？") 63 | 64 | # plugin_test(plugin='crazy_functions.Latex_Function->Latex翻译中文并重新编译PDF', main_input="2210.03629") 65 | 66 | -------------------------------------------------------------------------------- /tests/test_rag.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/binary-husky/gpt_academic/8c2143229113ad0953b4e4dfd2a543292ce65b14/tests/test_rag.py -------------------------------------------------------------------------------- /tests/test_safe_pickle.py: -------------------------------------------------------------------------------- 1 | def validate_path(): 2 | import os, sys 3 | os.path.dirname(__file__) 4 | root_dir_assume = os.path.abspath(os.path.dirname(__file__) + "/..") 5 | os.chdir(root_dir_assume) 6 | sys.path.append(root_dir_assume) 7 | validate_path() # validate path so you can run from base directory 8 | 9 | from crazy_functions.latex_fns.latex_pickle_io import objdump, objload 10 | from crazy_functions.latex_fns.latex_actions import LatexPaperFileGroup, LatexPaperSplit 11 | pfg = LatexPaperFileGroup() 12 | pfg.get_token_num = None 13 | pfg.target = "target_elem" 14 | x = objdump(pfg) 15 | t = objload() 16 | 17 | print(t.target) -------------------------------------------------------------------------------- /tests/test_searxng.py: -------------------------------------------------------------------------------- 1 | def validate_path(): 2 | import os, sys 3 | os.path.dirname(__file__) 4 | root_dir_assume = os.path.abspath(os.path.dirname(__file__) + "/..") 5 | os.chdir(root_dir_assume) 6 | sys.path.append(root_dir_assume) 7 | validate_path() # validate path so you can run from base directory 8 | 9 | from toolbox import get_conf 10 | import requests 11 | 12 | def searxng_request(query, proxies, categories='general', searxng_url=None, engines=None): 13 | url = 'http://localhost:50001/' 14 | 15 | if engines is None: 16 | engine = 'bing,' 17 | if categories == 'general': 18 | params = { 19 | 'q': query, # 搜索查询 20 | 'format': 'json', # 输出格式为JSON 21 | 'language': 'zh', # 搜索语言 22 | 'engines': engine, 23 | } 24 | elif categories == 'science': 25 | params = { 26 | 'q': query, # 搜索查询 27 | 'format': 'json', # 输出格式为JSON 28 | 'language': 'zh', # 搜索语言 29 | 'categories': 'science' 30 | } 31 | else: 32 | raise ValueError('不支持的检索类型') 33 | headers = { 34 | 'Accept-Language': 'zh-CN,zh;q=0.9', 35 | 'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.36', 36 | 'X-Forwarded-For': '112.112.112.112', 37 | 'X-Real-IP': '112.112.112.112' 38 | } 39 | results = [] 40 | response = requests.post(url, params=params, headers=headers, proxies=proxies, timeout=30) 41 | if response.status_code == 200: 42 | json_result = response.json() 43 | for result in json_result['results']: 44 | item = { 45 | "title": result.get("title", ""), 46 | "content": result.get("content", ""), 47 | "link": result["url"], 48 | } 49 | print(result['engines']) 50 | results.append(item) 51 | return results 52 | else: 53 | if response.status_code == 429: 54 | raise ValueError("Searxng（在线搜索服务）当前使用人数太多，请稍后。") 55 | else: 56 | raise ValueError("在线搜索失败，状态码: " + str(response.status_code) + '\t' + response.content.decode('utf-8')) 57 | res = searxng_request("vr environment", None, categories='science', searxng_url=None, engines=None) 58 | print(res) -------------------------------------------------------------------------------- /tests/test_social_helper.py: -------------------------------------------------------------------------------- 1 | """ 2 | 对项目中的各个插件进行测试。运行方法：直接运行 python tests/test_plugins.py 3 | """ 4 | 5 | import init_test 6 | import os, sys 7 | 8 | 9 | if __name__ == "__main__": 10 | from test_utils import plugin_test 11 | plugin_test( 12 | plugin='crazy_functions.Social_Helper->I人助手', 13 | main_input=""" 14 | 添加联系人： 15 | 艾德·史塔克：我的养父，他是临冬城的公爵。 16 | 凯特琳·史塔克：我的养母，她对我态度冷淡，因为我是私生子。 17 | 罗柏·史塔克：我的哥哥，他是北境的继承人。 18 | 艾莉亚·史塔克：我的妹妹，她和我关系亲密，性格独立坚强。 19 | 珊莎·史塔克：我的妹妹，她梦想成为一位淑女。 20 | 布兰·史塔克：我的弟弟，他有预知未来的能力。 21 | 瑞肯·史塔克：我的弟弟，他是个天真无邪的小孩。 22 | 山姆威尔·塔利：我的朋友，他在守夜人军团中与我并肩作战。 23 | 伊格瑞特：我的恋人，她是野人中的一员。 24 | """) 25 | -------------------------------------------------------------------------------- /tests/test_tts.py: -------------------------------------------------------------------------------- 1 | import edge_tts 2 | import os 3 | import httpx 4 | from toolbox import get_conf 5 | 6 | 7 | async def test_tts(): 8 | async with httpx.AsyncClient() as client: 9 | try: 10 | # Forward the request to the target service 11 | import tempfile 12 | import edge_tts 13 | import wave 14 | import uuid 15 | from pydub import AudioSegment 16 | voice = get_conf("EDGE_TTS_VOICE") 17 | tts = edge_tts.Communicate(text="测试", voice=voice) 18 | temp_folder = tempfile.gettempdir() 19 | temp_file_name = str(uuid.uuid4().hex) 20 | temp_file = os.path.join(temp_folder, f'{temp_file_name}.mp3') 21 | await tts.save(temp_file) 22 | try: 23 | mp3_audio = AudioSegment.from_file(temp_file, format="mp3") 24 | mp3_audio.export(temp_file, format="wav") 25 | with open(temp_file, 'rb') as wav_file: t = wav_file.read() 26 | except: 27 | raise RuntimeError("ffmpeg未安装，无法处理EdgeTTS音频。安装方法见`https://github.com/jiaaro/pydub#getting-ffmpeg-set-up`") 28 | except httpx.RequestError as e: 29 | raise RuntimeError(f"请求失败: {e}") 30 | 31 | if __name__ == "__main__": 32 | import asyncio 33 | asyncio.run(test_tts()) -------------------------------------------------------------------------------- /tests/test_utils.py: -------------------------------------------------------------------------------- 1 | from toolbox import get_conf 2 | from toolbox import set_conf 3 | from toolbox import set_multi_conf 4 | from toolbox import get_plugin_handle 5 | from toolbox import get_plugin_default_kwargs 6 | from toolbox import get_chat_handle 7 | from toolbox import get_chat_default_kwargs 8 | from functools import wraps 9 | import sys 10 | import os 11 | 12 | 13 | def chat_to_markdown_str(chat): 14 | result = "" 15 | for i, cc in enumerate(chat): 16 | result += f"\n\n{cc[0]}\n\n{cc[1]}" 17 | if i != len(chat) - 1: 18 | result += "\n\n---" 19 | return result 20 | 21 | 22 | def silence_stdout(func): 23 | @wraps(func) 24 | def wrapper(*args, **kwargs): 25 | _original_stdout = sys.stdout 26 | sys.stdout = open(os.devnull, "w") 27 | sys.stdout.reconfigure(encoding="utf-8") 28 | for q in func(*args, **kwargs): 29 | sys.stdout = _original_stdout 30 | yield q 31 | sys.stdout = open(os.devnull, "w") 32 | sys.stdout.reconfigure(encoding="utf-8") 33 | sys.stdout.close() 34 | sys.stdout = _original_stdout 35 | 36 | return wrapper 37 | 38 | 39 | def silence_stdout_fn(func): 40 | @wraps(func) 41 | def wrapper(*args, **kwargs): 42 | _original_stdout = sys.stdout 43 | sys.stdout = open(os.devnull, "w") 44 | sys.stdout.reconfigure(encoding="utf-8") 45 | result = func(*args, **kwargs) 46 | sys.stdout.close() 47 | sys.stdout = _original_stdout 48 | return result 49 | 50 | return wrapper 51 | 52 | 53 | class VoidTerminal: 54 | def __init__(self) -> None: 55 | pass 56 | 57 | 58 | vt = VoidTerminal() 59 | vt.get_conf = silence_stdout_fn(get_conf) 60 | vt.set_conf = silence_stdout_fn(set_conf) 61 | vt.set_multi_conf = silence_stdout_fn(set_multi_conf) 62 | vt.get_plugin_handle = silence_stdout_fn(get_plugin_handle) 63 | vt.get_plugin_default_kwargs = silence_stdout_fn(get_plugin_default_kwargs) 64 | vt.get_chat_handle = silence_stdout_fn(get_chat_handle) 65 | vt.get_chat_default_kwargs = silence_stdout_fn(get_chat_default_kwargs) 66 | vt.chat_to_markdown_str = chat_to_markdown_str 67 | ( 68 | proxies, 69 | WEB_PORT, 70 | LLM_MODEL, 71 | CONCURRENT_COUNT, 72 | AUTHENTICATION, 73 | CHATBOT_HEIGHT, 74 | LAYOUT, 75 | API_KEY, 76 | ) = vt.get_conf( 77 | "proxies", 78 | "WEB_PORT", 79 | "LLM_MODEL", 80 | "CONCURRENT_COUNT", 81 | "AUTHENTICATION", 82 | "CHATBOT_HEIGHT", 83 | "LAYOUT", 84 | "API_KEY", 85 | ) 86 | 87 | 88 | def plugin_test(main_input, plugin, advanced_arg=None, debug=True): 89 | from rich.live import Live 90 | from rich.markdown import Markdown 91 | 92 | vt.set_conf(key="API_KEY", value=API_KEY) 93 | vt.set_conf(key="LLM_MODEL", value=LLM_MODEL) 94 | 95 | plugin = vt.get_plugin_handle(plugin) 96 | plugin_kwargs = vt.get_plugin_default_kwargs() 97 | plugin_kwargs["main_input"] = main_input 98 | if advanced_arg is not None: 99 | plugin_kwargs["plugin_kwargs"] = advanced_arg 100 | if debug: 101 | my_working_plugin = (plugin)(**plugin_kwargs) 102 | else: 103 | my_working_plugin = silence_stdout(plugin)(**plugin_kwargs) 104 | 105 | with Live(Markdown(""), auto_refresh=False, vertical_overflow="visible") as live: 106 | for cookies, chat, hist, msg in my_working_plugin: 107 | md_str = vt.chat_to_markdown_str(chat) 108 | md = Markdown(md_str) 109 | live.update(md, refresh=True) 110 | -------------------------------------------------------------------------------- /tests/test_vector_plugins.py: -------------------------------------------------------------------------------- 1 | """ 2 | 对项目中的各个插件进行测试。运行方法：直接运行 python tests/test_plugins.py 3 | """ 4 | 5 | 6 | import os, sys 7 | 8 | 9 | def validate_path(): 10 | dir_name = os.path.dirname(__file__) 11 | root_dir_assume = os.path.abspath(dir_name + "/..") 12 | os.chdir(root_dir_assume) 13 | sys.path.append(root_dir_assume) 14 | 15 | 16 | validate_path() # 返回项目根路径 17 | 18 | if __name__ == "__main__": 19 | from tests.test_utils import plugin_test 20 | 21 | plugin_test(plugin="crazy_functions.知识库问答->知识库文件注入", main_input="./README.md") 22 | 23 | plugin_test( 24 | plugin="crazy_functions.知识库问答->读取知识库作答", 25 | main_input="What is the installation method？", 26 | ) 27 | 28 | plugin_test(plugin="crazy_functions.知识库问答->读取知识库作答", main_input="远程云服务器部署？") 29 | -------------------------------------------------------------------------------- /themes/base64.mjs: -------------------------------------------------------------------------------- 1 | // we have moved mermaid-related code to gradio-fix repository: binary-husky/gradio-fix@32150d0 2 | -------------------------------------------------------------------------------- /themes/common.py: -------------------------------------------------------------------------------- 1 | from functools import lru_cache 2 | from toolbox import get_conf 3 | CODE_HIGHLIGHT, ADD_WAIFU, LAYOUT = get_conf("CODE_HIGHLIGHT", "ADD_WAIFU", "LAYOUT") 4 | 5 | def inject_mutex_button_code(js_content): 6 | from crazy_functional import get_multiplex_button_functions 7 | fns = get_multiplex_button_functions() 8 | 9 | template = """ 10 | if (multiplex_sel === "{x}") { 11 | let _align_name_in_crazy_function_py = "{y}"; 12 | call_plugin_via_name(_align_name_in_crazy_function_py); 13 | return; 14 | } 15 | """ 16 | 17 | replacement = "" 18 | for fn in fns.keys(): 19 | if fn == "常规对话": continue 20 | replacement += template.replace("{x}", fn).replace("{y}", fns[fn]) 21 | js_content = js_content.replace("// REPLACE_EXTENDED_MULTIPLEX_FUNCTIONS_HERE", replacement) 22 | return js_content 23 | 24 | def minimize_js(common_js_path): 25 | try: 26 | import rjsmin, hashlib, glob, os 27 | # clean up old minimized js files, matching `common_js_path + '.min.*'` 28 | for old_min_js in glob.glob(common_js_path + '.min.*.js'): 29 | os.remove(old_min_js) 30 | # use rjsmin to minimize `common_js_path` 31 | c_jsmin = rjsmin.jsmin 32 | with open(common_js_path, "r", encoding='utf-8') as f: 33 | js_content = f.read() 34 | if common_js_path == "themes/common.js": 35 | js_content = inject_mutex_button_code(js_content) 36 | minimized_js_content = c_jsmin(js_content) 37 | # compute sha256 hash of minimized js content 38 | sha_hash = hashlib.sha256(minimized_js_content.encode()).hexdigest()[:8] 39 | minimized_js_path = common_js_path + '.min.' + sha_hash + '.js' 40 | # save to minimized js file 41 | with open(minimized_js_path, "w", encoding='utf-8') as f: 42 | f.write(minimized_js_content) 43 | # return minimized js file path 44 | return minimized_js_path 45 | except: 46 | return common_js_path 47 | 48 | @lru_cache 49 | def get_common_html_javascript_code(): 50 | js = "\n" 51 | common_js_path_list = [ 52 | "themes/common.js", 53 | "themes/theme.js", 54 | "themes/tts.js", 55 | "themes/init.js", 56 | "themes/welcome.js", 57 | ] 58 | 59 | if ADD_WAIFU: # 添加Live2D 60 | common_js_path_list += [ 61 | "themes/waifu_plugin/jquery.min.js", 62 | "themes/waifu_plugin/jquery-ui.min.js", 63 | ] 64 | 65 | for common_js_path in common_js_path_list: 66 | if '.min.' not in common_js_path: 67 | minimized_js_path = minimize_js(common_js_path) 68 | else: 69 | minimized_js_path = common_js_path 70 | jsf = f"file={minimized_js_path}" 71 | js += f"""\n""" 72 | 73 | if not ADD_WAIFU: 74 | js += """\n""" 75 | 76 | return js 77 | -------------------------------------------------------------------------------- /themes/cookies.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/binary-husky/gpt_academic/8c2143229113ad0953b4e4dfd2a543292ce65b14/themes/cookies.py -------------------------------------------------------------------------------- /themes/gradios.py: -------------------------------------------------------------------------------- 1 | import os 2 | import gradio as gr 3 | from toolbox import get_conf, ProxyNetworkActivate 4 | from loguru import logger 5 | 6 | CODE_HIGHLIGHT, ADD_WAIFU, LAYOUT = get_conf("CODE_HIGHLIGHT", "ADD_WAIFU", "LAYOUT") 7 | theme_dir = os.path.dirname(__file__) 8 | 9 | 10 | def dynamic_set_theme(THEME): 11 | set_theme = gr.themes.ThemeClass() 12 | with ProxyNetworkActivate("Download_Gradio_Theme"): 13 | logger.info("正在下载Gradio主题，请稍等。") 14 | try: 15 | if THEME.startswith("Huggingface-"): 16 | THEME = THEME.lstrip("Huggingface-") 17 | if THEME.startswith("huggingface-"): 18 | THEME = THEME.lstrip("huggingface-") 19 | set_theme = set_theme.from_hub(THEME.lower()) 20 | except: 21 | logger.error("下载Gradio主题时出现异常。") 22 | return set_theme 23 | 24 | 25 | def adjust_theme(): 26 | try: 27 | set_theme = gr.themes.ThemeClass() 28 | with ProxyNetworkActivate("Download_Gradio_Theme"): 29 | logger.info("正在下载Gradio主题，请稍等。") 30 | try: 31 | THEME = get_conf("THEME") 32 | if THEME.startswith("Huggingface-"): 33 | THEME = THEME.lstrip("Huggingface-") 34 | if THEME.startswith("huggingface-"): 35 | THEME = THEME.lstrip("huggingface-") 36 | set_theme = set_theme.from_hub(THEME.lower()) 37 | except: 38 | logger.error("下载Gradio主题时出现异常。") 39 | 40 | from themes.common import get_common_html_javascript_code 41 | js = get_common_html_javascript_code() 42 | 43 | if not hasattr(gr, "RawTemplateResponse"): 44 | gr.RawTemplateResponse = gr.routes.templates.TemplateResponse 45 | gradio_original_template_fn = gr.RawTemplateResponse 46 | 47 | def gradio_new_template_fn(*args, **kwargs): 48 | res = gradio_original_template_fn(*args, **kwargs) 49 | res.body = res.body.replace(b"", f"{js}".encode("utf8")) 50 | res.init_headers() 51 | return res 52 | 53 | gr.routes.templates.TemplateResponse = ( 54 | gradio_new_template_fn # override gradio template 55 | ) 56 | except Exception: 57 | set_theme = None 58 | logger.error("gradio版本较旧, 不能自定义字体和颜色。") 59 | return set_theme 60 | 61 | 62 | with open(os.path.join(theme_dir, "common.css"), "r", encoding="utf-8") as f: 63 | advanced_css = f.read() 64 | -------------------------------------------------------------------------------- /themes/green.js: -------------------------------------------------------------------------------- 1 | 2 | var academic_chat = null; 3 | 4 | var sliders = null; 5 | var rangeInputs = null; 6 | var numberInputs = null; 7 | 8 | function set_elements() { 9 | academic_chat = document.querySelector('gradio-app'); 10 | async function get_sliders() { 11 | sliders = document.querySelectorAll('input[type="range"]'); 12 | while (sliders.length == 0) { 13 | await new Promise(r => setTimeout(r, 100)); 14 | sliders = document.querySelectorAll('input[type="range"]'); 15 | } 16 | setSlider(); 17 | } 18 | get_sliders(); 19 | } 20 | 21 | function setSlider() { 22 | rangeInputs = document.querySelectorAll('input[type="range"]'); 23 | numberInputs = document.querySelectorAll('input[type="number"]') 24 | function setSliderRange() { 25 | var range = document.querySelectorAll('input[type="range"]'); 26 | range.forEach(range => { 27 | range.style.backgroundSize = (range.value - range.min) / (range.max - range.min) * 100 + '% 100%'; 28 | }); 29 | } 30 | setSliderRange(); 31 | rangeInputs.forEach(rangeInput => { 32 | rangeInput.addEventListener('input', setSliderRange); 33 | }); 34 | numberInputs.forEach(numberInput => { 35 | numberInput.addEventListener('input', setSliderRange); 36 | }) 37 | } 38 | 39 | window.addEventListener("DOMContentLoaded", () => { 40 | set_elements(); 41 | }); 42 | -------------------------------------------------------------------------------- /themes/gui_advanced_plugin_class.py: -------------------------------------------------------------------------------- 1 | import gradio as gr 2 | import json 3 | from toolbox import format_io, find_free_port, on_file_uploaded, on_report_generated, get_conf, ArgsGeneralWrapper, DummyWith 4 | 5 | def define_gui_advanced_plugin_class(plugins): 6 | # 定义新一代插件的高级参数区 7 | with gr.Floating(init_x="50%", init_y="50%", visible=False, width="30%", drag="top", elem_id="plugin_arg_menu"): 8 | with gr.Accordion("选择插件参数", open=True, elem_id="plugin_arg_panel"): 9 | for u in range(8): 10 | with gr.Row(): 11 | gr.Textbox(show_label=True, label="T1", placeholder="请输入", lines=1, visible=False, elem_id=f"plugin_arg_txt_{u}").style(container=False) 12 | for u in range(8): 13 | with gr.Row(): # PLUGIN_ARG_MENU 14 | gr.Dropdown(label="T1", value="请选择", choices=[], visible=True, elem_id=f"plugin_arg_drop_{u}", interactive=True) 15 | 16 | with gr.Row(): 17 | # 这个隐藏textbox负责装入当前弹出插件的属性 18 | gr.Textbox(show_label=False, placeholder="请输入", lines=1, visible=False, 19 | elem_id=f"invisible_current_pop_up_plugin_arg").style(container=False) 20 | usr_confirmed_arg = gr.Textbox(show_label=False, placeholder="请输入", lines=1, visible=False, 21 | elem_id=f"invisible_current_pop_up_plugin_arg_final").style(container=False) 22 | 23 | arg_confirm_btn = gr.Button("确认参数并执行", variant="stop") 24 | arg_confirm_btn.style(size="sm") 25 | 26 | arg_cancel_btn = gr.Button("取消", variant="stop") 27 | arg_cancel_btn.click(None, None, None, _js="""()=>close_current_pop_up_plugin()""") 28 | arg_cancel_btn.style(size="sm") 29 | 30 | arg_confirm_btn.click(None, None, None, _js="""()=>execute_current_pop_up_plugin()""") 31 | invisible_callback_btn_for_plugin_exe = gr.Button(r"未选定任何插件", variant="secondary", visible=False, elem_id="invisible_callback_btn_for_plugin_exe").style(size="sm") 32 | # 随变按钮的回调函数注册 33 | def route_switchy_bt_with_arg(request: gr.Request, input_order, *arg): 34 | arguments = {k:v for k,v in zip(input_order, arg)} # 重新梳理输入参数，转化为kwargs字典 35 | which_plugin = arguments.pop('new_plugin_callback') # 获取需要执行的插件名称 36 | if which_plugin in [r"未选定任何插件"]: return 37 | usr_confirmed_arg = arguments.pop('usr_confirmed_arg') # 获取插件参数 38 | arg_confirm: dict = {} 39 | usr_confirmed_arg_dict = json.loads(usr_confirmed_arg) # 读取插件参数 40 | for arg_name in usr_confirmed_arg_dict: 41 | arg_confirm.update({arg_name: str(usr_confirmed_arg_dict[arg_name]['user_confirmed_value'])}) 42 | 43 | if plugins[which_plugin].get("Class", None) is not None: # 获取插件执行函数 44 | plugin_obj = plugins[which_plugin]["Class"] 45 | plugin_exe = plugin_obj.execute 46 | else: 47 | plugin_exe = plugins[which_plugin]["Function"] 48 | 49 | arguments['plugin_advanced_arg'] = arg_confirm # 更新高级参数输入区的参数 50 | if arg_confirm.get('main_input', None) is not None: # 更新主输入区的参数 51 | arguments['txt'] = arg_confirm['main_input'] 52 | 53 | # 万事俱备，开始执行 54 | yield from ArgsGeneralWrapper(plugin_exe)(request, *arguments.values()) 55 | 56 | return invisible_callback_btn_for_plugin_exe, route_switchy_bt_with_arg, usr_confirmed_arg 57 | 58 | -------------------------------------------------------------------------------- /themes/svg/arxiv.svg: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | Layer 1 5 | 6 | 7 | -------------------------------------------------------------------------------- /themes/svg/box.svg: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /themes/svg/brain.svg: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | Layer 1 5 | 6 | 7 | 8 | -------------------------------------------------------------------------------- /themes/svg/check.svg: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /themes/svg/conf.svg: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | Layer 1 5 | 6 | 7 | 8 | -------------------------------------------------------------------------------- /themes/svg/default.svg: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /themes/svg/doc.svg: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | Layer 1 5 | 6 | 7 | 8 | 9 | -------------------------------------------------------------------------------- /themes/svg/img.svg: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | Layer 1 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | -------------------------------------------------------------------------------- /themes/svg/location.svg: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /themes/svg/mm.svg: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | Layer 1 5 | 6 | 7 | 8 | 9 | 10 | -------------------------------------------------------------------------------- /themes/svg/polish.svg: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | Layer 1 5 | 6 | 7 | -------------------------------------------------------------------------------- /themes/svg/tts.svg: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | Layer 1 5 | 6 | 7 | -------------------------------------------------------------------------------- /themes/svg/vt.svg: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | Layer 1 5 | 6 | 7 | 8 | -------------------------------------------------------------------------------- /themes/theme.js: -------------------------------------------------------------------------------- 1 | async function try_load_previous_theme(){ 2 | if (getCookie("js_theme_selection_cookie")) { 3 | theme_selection = getCookie("js_theme_selection_cookie"); 4 | let css = localStorage.getItem('theme-' + theme_selection); 5 | if (css) { 6 | change_theme(theme_selection, css); 7 | } 8 | } 9 | } 10 | 11 | async function change_theme(theme_selection, css) { 12 | if (theme_selection.length==0) { 13 | try_load_previous_theme(); 14 | return; 15 | } 16 | 17 | var existingStyles = document.querySelectorAll("body > gradio-app > div > style") 18 | for (var i = 0; i < existingStyles.length; i++) { 19 | var style = existingStyles[i]; 20 | style.parentNode.removeChild(style); 21 | } 22 | var existingStyles = document.querySelectorAll("style[data-loaded-css]"); 23 | for (var i = 0; i < existingStyles.length; i++) { 24 | var style = existingStyles[i]; 25 | style.parentNode.removeChild(style); 26 | } 27 | 28 | setCookie("js_theme_selection_cookie", theme_selection, 3); 29 | localStorage.setItem('theme-' + theme_selection, css); 30 | 31 | var styleElement = document.createElement('style'); 32 | styleElement.setAttribute('data-loaded-css', 'placeholder'); 33 | styleElement.innerHTML = css; 34 | document.body.appendChild(styleElement); 35 | } 36 | 37 | 38 | // // 记录本次的主题切换 39 | // async function change_theme_prepare(theme_selection, secret_css) { 40 | // setCookie("js_theme_selection_cookie", theme_selection, 3); 41 | // } -------------------------------------------------------------------------------- /themes/waifu_plugin/autoload.js: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/binary-husky/gpt_academic/8c2143229113ad0953b4e4dfd2a543292ce65b14/themes/waifu_plugin/autoload.js -------------------------------------------------------------------------------- /themes/waifu_plugin/flat-ui-icons-regular.eot: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/binary-husky/gpt_academic/8c2143229113ad0953b4e4dfd2a543292ce65b14/themes/waifu_plugin/flat-ui-icons-regular.eot -------------------------------------------------------------------------------- /themes/waifu_plugin/flat-ui-icons-regular.ttf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/binary-husky/gpt_academic/8c2143229113ad0953b4e4dfd2a543292ce65b14/themes/waifu_plugin/flat-ui-icons-regular.ttf 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